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asLody / SandHookAndroid ART Hook/Native Inline Hook/Single Instruction Hook - support 4.4 - 11.0 32/64 bit - Xposed API Compat
faragon / Libsrtlibsrt is a C library for writing fast and safe C code, faster. It provides string, vector, bit set, set, map, hash set, and hash map handling. Suitable for soft and hard real-time. Allows both heap and stack allocation. *BETA* (API still can change: suggestions are welcome)
philnash / Bitly🗜 A Ruby wrapper for the bit.ly API
chrisneagu / FTC Skystone Dark Angels Romania 2020NOTICE This repository contains the public FTC SDK for the SKYSTONE (2019-2020) competition season. If you are looking for the current season's FTC SDK software, please visit the new and permanent home of the public FTC SDK: FtcRobotController repository Welcome! This GitHub repository contains the source code that is used to build an Android app to control a FIRST Tech Challenge competition robot. To use this SDK, download/clone the entire project to your local computer. Getting Started If you are new to robotics or new to the FIRST Tech Challenge, then you should consider reviewing the FTC Blocks Tutorial to get familiar with how to use the control system: FTC Blocks Online Tutorial Even if you are an advanced Java programmer, it is helpful to start with the FTC Blocks tutorial, and then migrate to the OnBot Java Tool or to Android Studio afterwards. Downloading the Project If you are an Android Studio programmer, there are several ways to download this repo. Note that if you use the Blocks or OnBot Java Tool to program your robot, then you do not need to download this repository. If you are a git user, you can clone the most current version of the repository: git clone https://github.com/FIRST-Tech-Challenge/SKYSTONE.git Or, if you prefer, you can use the "Download Zip" button available through the main repository page. Downloading the project as a .ZIP file will keep the size of the download manageable. You can also download the project folder (as a .zip or .tar.gz archive file) from the Downloads subsection of the Releases page for this repository. Once you have downloaded and uncompressed (if needed) your folder, you can use Android Studio to import the folder ("Import project (Eclipse ADT, Gradle, etc.)"). Getting Help User Documentation and Tutorials FIRST maintains online documentation with information and tutorials on how to use the FIRST Tech Challenge software and robot control system. You can access this documentation using the following link: SKYSTONE Online Documentation Note that the online documentation is an "evergreen" document that is constantly being updated and edited. It contains the most current information about the FIRST Tech Challenge software and control system. Javadoc Reference Material The Javadoc reference documentation for the FTC SDK is now available online. Click on the following link to view the FTC SDK Javadoc documentation as a live website: FTC Javadoc Documentation Documentation for the FTC SDK is also included with this repository. There is a subfolder called "doc" which contains several subfolders: The folder "apk" contains the .apk files for the FTC Driver Station and FTC Robot Controller apps. The folder "javadoc" contains the JavaDoc user documentation for the FTC SDK. Online User Forum For technical questions regarding the Control System or the FTC SDK, please visit the FTC Technology forum: FTC Technology Forum Release Information Version 5.5 (20200824-090813) Version 5.5 requires Android Studio 4.0 or later. New features Adds support for calling custom Java classes from Blocks OpModes (fixes SkyStone issue #161). Classes must be in the org.firstinspires.ftc.teamcode package. Methods must be public static and have no more than 21 parameters. Parameters declared as OpMode, LinearOpMode, Telemetry, and HardwareMap are supported and the argument is provided automatically, regardless of the order of the parameters. On the block, the sockets for those parameters are automatically filled in. Parameters declared as char or java.lang.Character will accept any block that returns text and will only use the first character in the text. Parameters declared as boolean or java.lang.Boolean will accept any block that returns boolean. Parameters declared as byte, java.lang.Byte, short, java.lang.Short, int, java.lang.Integer, long, or java.lang.Long, will accept any block that returns a number and will round that value to the nearest whole number. Parameters declared as float, java.lang.Float, double, java.lang.Double will accept any block that returns a number. Adds telemetry API method for setting display format Classic Monospace HTML (certain tags only) Adds blocks support for switching cameras. Adds Blocks support for TensorFlow Object Detection with a custom model. Adds support for uploading a custom TensorFlow Object Detection model in the Manage page, which is especially useful for Blocks and OnBotJava users. Shows new Control Hub blink codes when the WiFi band is switched using the Control Hub's button (only possible on Control Hub OS 1.1.2) Adds new warnings which can be disabled in the Advanced RC Settings Mismatched app versions warning Unnecessary 2.4 GHz WiFi usage warning REV Hub is running outdated firmware (older than version 1.8.2) Adds support for Sony PS4 gamepad, and reworks how gamepads work on the Driver Station Removes preference which sets gamepad type based on driver position. Replaced with menu which allows specifying type for gamepads with unknown VID and PID Attempts to auto-detect gamepad type based on USB VID and PID If gamepad VID and PID is not known, use type specified by user for that VID and PID If gamepad VID and PID is not known AND the user has not specified a type for that VID and PID, an educated guess is made about how to map the gamepad Driver Station will now attempt to automatically recover from a gamepad disconnecting, and re-assign it to the position it was assigned to when it dropped If only one gamepad is assigned and it drops: it can be recovered If two gamepads are assigned, and have different VID/PID signatures, and only one drops: it will be recovered If two gamepads are assigned, and have different VID/PID signatures, and BOTH drop: both will be recovered If two gamepads are assigned, and have the same VID/PID signatures, and only one drops: it will be recovered If two gamepads are assigned, and have the same VID/PID signatures, and BOTH drop: neither will be recovered, because of the ambiguity of the gamepads when they re-appear on the USB bus. There is currently one known edge case: if there are two gamepads with the same VID/PID signature plugged in, but only one is assigned, and they BOTH drop, it's a 50-50 chance of which one will be chosen for automatic recovery to the assigned position: it is determined by whichever one is re-enumerated first by the USB bus controller. Adds landscape user interface to Driver Station New feature: practice timer with audio cues New feature (Control Hub only): wireless network connection strength indicator (0-5 bars) New feature (Control Hub only): tapping on the ping/channel display will switch to an alternate display showing radio RX dBm and link speed (tap again to switch back) The layout will NOT autorotate. You can switch the layout from the Driver Station's settings menu. Breaking changes Removes support for Android versions 4.4 through 5.1 (KitKat and Lollipop). The minSdkVersion is now 23. Removes the deprecated LinearOpMode methods waitOneFullHardwareCycle() and waitForNextHardwareCycle() Enhancements Handles RS485 address of Control Hub automatically The Control Hub is automatically given a reserved address Existing configuration files will continue to work All addresses in the range of 1-10 are still available for Expansion Hubs The Control Hub light will now normally be solid green, without blinking to indicate the address The Control Hub will not be shown on the Expansion Hub Address Change settings page Improves REV Hub firmware updater The user can now choose between all available firmware update files Version 1.8.2 of the REV Hub firmware is bundled into the Robot Controller app. Text was added to clarify that Expansion Hubs can only be updated via USB. Firmware update speed was reduced to improve reliability Allows REV Hub firmware to be updated directly from the Manage webpage Improves log viewer on Robot Controller Horizontal scrolling support (no longer word wrapped) Supports pinch-to-zoom Uses a monospaced font Error messages are highlighted New color scheme Attempts to force-stop a runaway/stuck OpMode without restarting the entire app Not all types of runaway conditions are stoppable, but if the user code attempts to talk to hardware during the runaway, the system should be able to capture it. Makes various tweaks to the Self Inspect screen Renames "OS version" entry to "Android version" Renames "WiFi Direct Name" to "WiFi Name" Adds Control Hub OS version, when viewing the report of a Control Hub Hides the airplane mode entry, when viewing the report of a Control Hub Removes check for ZTE Speed Channel Changer Shows firmware version for all Expansion and Control Hubs Reworks network settings portion of Manage page All network settings are now applied with a single click The WiFi Direct channel of phone-based Robot Controllers can now be changed from the Manage page WiFi channels are filtered by band (2.4 vs 5 GHz) and whether they overlap with other channels The current WiFi channel is pre-selected on phone-based Robot Controllers, and Control Hubs running OS 1.1.2 or later. On Control Hubs running OS 1.1.2 or later, you can choose to have the system automatically select a channel on the 5 GHz band Improves OnBotJava New light and dark themes replace the old themes (chaos, github, chrome,...) the new default theme is light and will be used when you first update to this version OnBotJava now has a tabbed editor Read-only offline mode Improves function of "exit" menu item on Robot Controller and Driver Station Now guaranteed to be fully stopped and unloaded from memory Shows a warning message if a LinearOpMode exists prematurely due to failure to monitor for the start condition Improves error message shown when the Driver Station and Robot Controller are incompatible with each other Driver Station OpMode Control Panel now disabled while a Restart Robot is in progress Disables advanced settings related to WiFi direct when the Robot Controller is a Control Hub. Tint phone battery icons on Driver Station when low/critical. Uses names "Control Hub Portal" and "Control Hub" (when appropriate) in new configuration files Improve I2C read performance Very large improvement on Control Hub; up to ~2x faster with small (e.g. 6 byte) reads Not as apparent on Expansion Hubs connected to a phone Update/refresh build infrastructure Update to 'androidx' support library from 'com.android.support:appcompat', which is end-of-life Update targetSdkVersion and compileSdkVersion to 28 Update Android Studio's Android plugin to latest Fix reported build timestamp in 'About' screen Add sample illustrating manual webcam use: ConceptWebcam Bug fixes Fixes SkyStone issue #248 Fixes SkyStone issue #232 and modifies bulk caching semantics to allow for cache-preserving MANUAL/AUTO transitions. Improves performance when REV 2M distance sensor is unplugged Improves readability of Toast messages on certain devices Allows a Driver Station to connect to a Robot Controller after another has disconnected Improves generation of fake serial numbers for UVC cameras which do not provide a real serial number Previously some devices would assign such cameras a serial of 0:0 and fail to open and start streaming Fixes ftc_app issue #638. Fixes a slew of bugs with the Vuforia camera monitor including: Fixes bug where preview could be displayed with a wonky aspect ratio Fixes bug where preview could be cut off in landscape Fixes bug where preview got totally messed up when rotating phone Fixes bug where crosshair could drift off target when using webcams Fixes issue in UVC driver on some devices (ftc_app 681) if streaming was started/stopped multiple times in a row Issue manifested as kernel panic on devices which do not have this kernel patch. On affected devices which do have the patch, the issue was manifest as simply a failure to start streaming. The Tech Team believes that the root cause of the issue is a bug in the Linux kernel XHCI driver. A workaround was implemented in the SDK UVC driver. Fixes bug in UVC driver where often half the frames from the camera would be dropped (e.g. only 15FPS delivered during a streaming session configured for 30FPS). Fixes issue where TensorFlow Object Detection would show results whose confidence was lower than the minimum confidence parameter. Fixes a potential exploitation issue of CVE-2019-11358 in OnBotJava Fixes changing the address of an Expansion Hub with additional Expansion Hubs connected to it Preserves the Control Hub's network connection when "Restart Robot" is selected Fixes issue where device scans would fail while the Robot was restarting Fix RenderScript usage Use androidx.renderscript variant: increased compatibility Use RenderScript in Java mode, not native: simplifies build Fixes webcam-frame-to-bitmap conversion problem: alpha channel wasn't being initialized, only R, G, & B Fixes possible arithmetic overflow in Deadline Fixes deadlock in Vuforia webcam support which could cause 5-second delays when stopping OpMode Version 5.4 (20200108-101156) Fixes SkyStone issue #88 Adds an inspection item that notes when a robot controller (Control Hub) is using the factory default password. Fixes SkyStone issue #61 Fixes SkyStone issue #142 Fixes ftc_app issue #417 by adding more current and voltage monitoring capabilities for REV Hubs. Fixes a crash sometimes caused by OnBotJava activity Improves OnBotJava autosave functionality ftc_app #738 Fixes system responsiveness issue when an Expansion Hub is disconnected Fixes issue where IMU initialization could prevent Op Modes from stopping Fixes issue where AndroidTextToSpeech.speak() would fail if it was called too early Adds telemetry.speak() methods and blocks, which cause the Driver Station (if also updated) to speak text Adds and improves Expansion Hub-related warnings Improves Expansion Hub low battery warning Displays the warning immediately after the hub reports it Specifies whether the condition is current or occurred temporarily during an OpMode run Displays which hubs reported low battery Displays warning when hub loses and regains power during an OpMode run Fixes the hub's LED pattern after this condition Displays warning when Expansion Hub is not responding to commands Specifies whether the condition is current or occurred temporarily during an OpMode run Clarifies warning when Expansion Hub is not present at startup Specifies that this condition requires a Robot Restart before the hub can be used. The hub light will now accurately reflect this state Improves logging and reduces log spam during these conditions Syncs the Control Hub time and timezone to a connected web browser programming the robot, if a Driver Station is not available. Adds bulk read functionality for REV Hubs A bulk caching mode must be set at the Hub level with LynxModule#setBulkCachingMode(). This applies to all relevant SDK hardware classes that reference that Hub. The following following Hub bulk caching modes are available: BulkCachingMode.OFF (default): All hardware calls operate as usual. Bulk data can read through LynxModule#getBulkData() and processed manually. BulkCachingMode.AUTO: Applicable hardware calls are served from a bulk read cache that is cleared/refreshed automatically to ensure identical commands don't hit the same cache. The cache can also be cleared manually with LynxModule#clearBulkCache(), although this is not recommended. (advanced users) BulkCachingMode.MANUAL: Same as BulkCachingMode.AUTO except the cache is never cleared automatically. To avoid getting stale data, the cache must be manually cleared at the beginning of each loop body or as the user deems appropriate. Removes PIDF Annotation values added in Rev 5.3 (to AndyMark, goBILDA and TETRIX motor configurations). The new motor types will still be available but their Default control behavior will revert back to Rev 5.2 Adds new ConceptMotorBulkRead sample Opmode to demonstrate and compare Motor Bulk-Read modes for reducing I/O latencies. Version 5.3 (20191004-112306) Fixes external USB/UVC webcam support Makes various bugfixes and improvements to Blocks page, including but not limited to: Many visual tweaks Browser zoom and window resize behave better Resizing the Java preview pane works better and more consistently across browsers The Java preview pane consistently gets scrollbars when needed The Java preview pane is hidden by default on phones Internet Explorer 11 should work Large dropdown lists display properly on lower res screens Disabled buttons are now visually identifiable as disabled A warning is shown if a user selects a TFOD sample, but their device is not compatible Warning messages in a Blocks op mode are now visible by default. Adds goBILDA 5201 and 5202 motors to Robot Configurator Adds PIDF Annotation values to AndyMark, goBILDA and TETRIX motor configurations. This has the effect of causing the RUN_USING_ENCODERS and RUN_TO_POSITION modes to use PIDF vs PID closed loop control on these motors. This should provide more responsive, yet stable, speed control. PIDF adds Feedforward control to the basic PID control loop. Feedforward is useful when controlling a motor's speed because it "anticipates" how much the control voltage must change to achieve a new speed set-point, rather than requiring the integrated error to change sufficiently. The PIDF values were chosen to provide responsive, yet stable, speed control on a lightly loaded motor. The more heavily a motor is loaded (drag or friction), the more noticable the PIDF improvement will be. Fixes startup crash on Android 10 Fixes ftc_app issue #712 (thanks to FROGbots-4634) Fixes ftc_app issue #542 Allows "A" and lowercase letters when naming device through RC and DS apps. Version 5.2 (20190905-083277) Fixes extra-wide margins on settings activities, and placement of the new configuration button Adds Skystone Vuforia image target data. Includes sample Skystone Vuforia Navigation op modes (Java). Includes sample Skystone Vuforia Navigation op modes (Blocks). Adds TensorFlow inference model (.tflite) for Skystone game elements. Includes sample Skystone TensorFlow op modes (Java). Includes sample Skystone TensorFlow op modes (Blocks). Removes older (season-specific) sample op modes. Includes 64-bit support (to comply with Google Play requirements). Protects against Stuck OpModes when a Restart Robot is requested. (Thanks to FROGbots-4634) (ftc_app issue #709) Blocks related changes: Fixes bug with blocks generated code when hardware device name is a java or javascript reserved word. Shows generated java code for blocks, even when hardware items are missing from the active configuration. Displays warning icon when outdated Vuforia and TensorFlow blocks are used (SkyStone issue #27) Version 5.1 (20190820-222104) Defines default PIDF parameters for the following motors: REV Core Hex Motor REV 20:1 HD Hex Motor REV 40:1 HD Hex Motor Adds back button when running on a device without a system back button (such as a Control Hub) Allows a REV Control Hub to update the firmware on a REV Expansion Hub via USB Fixes SkyStone issue #9 Fixes ftc_app issue #715 Prevents extra DS User clicks by filtering based on current state. Prevents incorrect DS UI state changes when receiving new OpMode list from RC Adds support for REV Color Sensor V3 Adds a manual-refresh DS Camera Stream for remotely viewing RC camera frames. To show the stream on the DS, initialize but do not run a stream-enabled opmode, select the Camera Stream option in the DS menu, and tap the image to refresh. This feature is automatically enabled when using Vuforia or TFOD—no additional RC configuration is required for typical use cases. To hide the stream, select the same menu item again. Note that gamepads are disabled and the selected opmode cannot be started while the stream is open as a safety precaution. To use custom streams, consult the API docs for CameraStreamServer#setSource and CameraStreamSource. Adds many Star Wars sounds to RobotController resources. Added SKYSTONE Sounds Chooser Sample Program. Switches out startup, connect chimes, and error/warning sounds for Star Wars sounds Updates OnBot Java to use a WebSocket for communication with the robot The OnBot Java page no longer has to do a full refresh when a user switches from editing one file to another Known issues: Camera Stream The Vuforia camera stream inherits the issues present in the phone preview (namely ftc_app issue #574). This problem does not affect the TFOD camera stream even though it receives frames from Vuforia. The orientation of the stream frames may not always match the phone preview. For now, these frames may be rotated manually via a custom CameraStreamSource if desired. OnBotJava Browser back button may not always work correctly It's possible for a build to be queued, but not started. The OnBot Java build console will display a warning if this occurs. A user might not realize they are editing a different file if the user inadvertently switches from one file to another since this switch is now seamless. The name of the currently open file is displayed in the browser tab. Version 5.0 (built on 19.06.14) Support for the REV Robotics Control Hub. Adds a Java preview pane to the Blocks editor. Adds a new offline export feature to the Blocks editor. Display wifi channel in Network circle on Driver Station. Adds calibration for Logitech C270 Updates build tooling and target SDK. Compliance with Google's permissions infrastructure (Required after build tooling update). Keep Alives to mitigate the Motorola wifi scanning problem. Telemetry substitute no longer necessary. Improves Vuforia error reporting. Fixes ftctechnh/ftc_app issues 621, 713. Miscellaneous bug fixes and improvements. Version 4.3 (built on 18.10.31) Includes missing TensorFlow-related libraries and files. Version 4.2 (built on 18.10.30) Includes fix to avoid deadlock situation with WatchdogMonitor which could result in USB communication errors. Comm error appeared to require that user disconnect USB cable and restart the Robot Controller app to recover. robotControllerLog.txt would have error messages that included the words "E RobotCore: lynx xmit lock: #### abandoning lock:" Includes fix to correctly list the parent module address for a REV Robotics Expansion Hub in a configuration (.xml) file. Bug in versions 4.0 and 4.1 would incorrect list the address module for a parent REV Robotics device as "1". If the parent module had a higher address value than the daisy-chained module, then this bug would prevent the Robot Controller from communicating with the downstream Expansion Hub. Added requirement for ACCESS_COARSE_LOCATION to allow a Driver Station running Android Oreo to scan for Wi-Fi Direct devices. Added google() repo to build.gradle because aapt2 must be downloaded from the google() repository beginning with version 3.2 of the Android Gradle Plugin. Important Note: Android Studio users will need to be connected to the Internet the first time build the ftc_app project. Internet connectivity is required for the first build so the appropriate files can be downloaded from the Google repository. Users should not need to be connected to the Internet for subsequent builds. This should also fix buid issue where Android Studio would complain that it "Could not find com.android.tools.lint:lint-gradle:26.1.4" (or similar). Added support for REV Spark Mini motor controller as part of the configuration menu for a servo/PWM port on the REV Expansion Hub. Provide examples for playing audio files in an Op Mode. Block Development Tool Changes Includes a fix for a problem with the Velocity blocks that were reported in the FTC Technology forum (Blocks Programming subforum). Change the "Save completed successfully." message to a white color so it will contrast with a green background. Fixed the "Download image" feature so it will work if there are text blocks in the op mode. Introduce support for Google's TensorFlow Lite technology for object detetion for 2018-2019 game. TensorFlow lite can recognize Gold Mineral and Silver Mineral from 2018-2019 game. Example Java and Block op modes are included to show how to determine the relative position of the gold block (left, center, right). Version 4.1 (released on 18.09.24) Changes include: Fix to prevent crash when deprecated configuration annotations are used. Change to allow FTC Robot Controller APK to be auto-updated using FIRST Global Control Hub update scripts. Removed samples for non supported / non legal hardware. Improvements to Telemetry.addData block with "text" socket. Updated Blocks sample op mode list to include Rover Ruckus Vuforia example. Update SDK library version number. Version 4.0 (released on 18.09.12) Changes include: Initial support for UVC compatible cameras If UVC camera has a unique serial number, RC will detect and enumerate by serial number. If UVC camera lacks a unique serial number, RC will only support one camera of that type connected. Calibration settings for a few cameras are included (see TeamCode/src/main/res/xml/teamwebcamcalibrations.xml for details). User can upload calibration files from Program and Manage web interface. UVC cameras seem to draw a fair amount of electrical current from the USB bus. This does not appear to present any problems for the REV Robotics Control Hub. This does seem to create stability problems when using some cameras with an Android phone-based Robot Controller. FTC Tech Team is investigating options to mitigate this issue with the phone-based Robot Controllers. Updated sample Vuforia Navigation and VuMark Op Modes to demonstrate how to use an internal phone-based camera and an external UVC webcam. Support for improved motor control. REV Robotics Expansion Hub firmware 1.8 and greater will support a feed forward mechanism for closed loop motor control. FTC SDK has been modified to support PIDF coefficients (proportional, integral, derivative, and feed forward). FTC Blocks development tool modified to include PIDF programming blocks. Deprecated older PID-related methods and variables. REV's 1.8.x PIDF-related changes provide a more linear and accurate way to control a motor. Wireless Added 5GHz support for wireless channel changing for those devices that support it. Tested with Moto G5 and E4 phones. Also tested with other (currently non-approved) phones such as Samsung Galaxy S8. Improved Expansion Hub firmware update support in Robot Controller app Changes to make the system more robust during the firmware update process (when performed through Robot Controller app). User no longer has to disconnect a downstream daisy-chained Expansion Hub when updating an Expansion Hub's firmware. If user is updating an Expansion Hub's firmware through a USB connection, he/she does not have to disconnect RS485 connection to other Expansion Hubs. The user still must use a USB connection to update an Expansion Hub's firmware. The user cannot update the Expansion Hub firmware for a downstream device that is daisy chained through an RS485 connection. If an Expansion Hub accidentally gets "bricked" the Robot Controller app is now more likely to recognize the Hub when it scans the USB bus. Robot Controller app should be able to detect an Expansion Hub, even if it accidentally was bricked in a previous update attempt. Robot Controller app should be able to install the firmware onto the Hub, even if if accidentally was bricked in a previous update attempt. Resiliency FTC software can detect and enable an FTDI reset feature that is available with REV Robotics v1.8 Expansion Hub firmware and greater. When enabled, the Expansion Hub can detect if it hasn't communicated with the Robot Controller over the FTDI (USB) connection. If the Hub hasn't heard from the Robot Controller in a while, it will reset the FTDI connection. This action helps system recover from some ESD-induced disruptions. Various fixes to improve reliability of FTC software. Blocks Fixed errors with string and list indices in blocks export to java. Support for USB connected UVC webcams. Refactored optimized Blocks Vuforia code to support Rover Ruckus image targets. Added programming blocks to support PIDF (proportional, integral, derivative and feed forward) motor control. Added formatting options (under Telemetry and Miscellaneous categories) so user can set how many decimal places to display a numerical value. Support to play audio files (which are uploaded through Blocks web interface) on Driver Station in addition to the Robot Controller. Fixed bug with Download Image of Blocks feature. Support for REV Robotics Blinkin LED Controller. Support for REV Robotics 2m Distance Sensor. Added support for a REV Touch Sensor (no longer have to configure as a generic digital device). Added blocks for DcMotorEx methods. These are enhanced methods that you can use when supported by the motor controller hardware. The REV Robotics Expansion Hub supports these enhanced methods. Enhanced methods include methods to get/set motor velocity (in encoder pulses per second), get/set PIDF coefficients, etc.. Modest Improvements in Logging Decrease frequency of battery checker voltage statements. Removed non-FTC related log statements (wherever possible). Introduced a "Match Logging" feature. Under "Settings" a user can enable/disable this feature (it's disabled by default). If enabled, user provides a "Match Number" through the Driver Station user interface (top of the screen). The Match Number is used to create a log file specifically with log statements from that particular Op Mode run. Match log files are stored in /sdcard/FIRST/matlogs on the Robot Controller. Once an op mode run is complete, the Match Number is cleared. This is a convenient way to create a separate match log with statements only related to a specific op mode run. New Devices Support for REV Robotics Blinkin LED Controller. Support for REV Robotics 2m Distance Sensor. Added configuration option for REV 20:1 HD Hex Motor. Added support for a REV Touch Sensor (no longer have to configure as a generic digital device). Miscellaneous Fixed some errors in the definitions for acceleration and velocity in our javadoc documentation. Added ability to play audio files on Driver Station When user is configuring an Expansion Hub, the LED on the Expansion Hub will change blink pattern (purple-cyan) to indicate which Hub is currently being configured. Renamed I2cSensorType to I2cDeviceType. Added an external sample Op Mode that demonstrates localization using 2018-2019 (Rover Ruckus presented by QualComm) Vuforia targets. Added an external sample Op Mode that demonstrates how to use the REV Robotics 2m Laser Distance Sensor. Added an external sample Op Mode that demonstrates how to use the REV Robotics Blinkin LED Controller. Re-categorized external Java sample Op Modes to "TeleOp" instead of "Autonomous". Known issues: Initial support for UVC compatible cameras UVC cameras seem to draw significant amount of current from the USB bus. This does not appear to present any problems for the REV Robotics Control Hub. This does seem to create stability problems when using some cameras with an Android phone-based Robot Controller. FTC Tech Team is investigating options to mitigate this issue with the phone-based Robot Controllers. There might be a possible deadlock which causes the RC to become unresponsive when using a UVC webcam with a Nougat Android Robot Controller. Wireless When user selects a wireless channel, this channel does not necessarily persist if the phone is power cycled. Tech Team is hoping to eventually address this issue in a future release. Issue has been present since apps were introduced (i.e., it is not new with the v4.0 release). Wireless channel is not currently displayed for WiFi Direct connections. Miscellaneous The blink indication feature that shows which Expansion Hub is currently being configured does not work for a newly created configuration file. User has to first save a newly created configuration file and then close and re-edit the file in order for blink indicator to work. Version 3.6 (built on 17.12.18) Changes include: Blocks Changes Uses updated Google Blockly software to allow users to edit their op modes on Apple iOS devices (including iPad and iPhone). Improvement in Blocks tool to handle corrupt op mode files. Autonomous op modes should no longer get switched back to tele-op after re-opening them to be edited. The system can now detect type mismatches during runtime and alert the user with a message on the Driver Station. Updated javadoc documentation for setPower() method to reflect correct range of values (-1 to +1). Modified VuforiaLocalizerImpl to allow for user rendering of frames Added a user-overrideable onRenderFrame() method which gets called by the class's renderFrame() method. Version 3.5 (built on 17.10.30) Changes with version 3.5 include: Introduced a fix to prevent random op mode stops, which can occur after the Robot Controller app has been paused and then resumed (for example, when a user temporarily turns off the display of the Robot Controller phone, and then turns the screen back on). Introduced a fix to prevent random op mode stops, which were previously caused by random peer disconnect events on the Driver Station. Fixes issue where log files would be closed on pause of the RC or DS, but not re-opened upon resume. Fixes issue with battery handler (voltage) start/stop race. Fixes issue where Android Studio generated op modes would disappear from available list in certain situations. Fixes problem where OnBot Java would not build on REV Robotics Control Hub. Fixes problem where OnBot Java would not build if the date and time on the Robot Controller device was "rewound" (set to an earlier date/time). Improved error message on OnBot Java that occurs when renaming a file fails. Removed unneeded resources from android.jar binaries used by OnBot Java to reduce final size of Robot Controller app. Added MR_ANALOG_TOUCH_SENSOR block to Blocks Programming Tool. Version 3.4 (built on 17.09.06) Changes with version 3.4 include: Added telemetry.update() statement for BlankLinearOpMode template. Renamed sample Block op modes to be more consistent with Java samples. Added some additional sample Block op modes. Reworded OnBot Java readme slightly. Version 3.3 (built on 17.09.04) This version of the software includes improves for the FTC Blocks Programming Tool and the OnBot Java Programming Tool. Changes with verion 3.3 include: Android Studio ftc_app project has been updated to use Gradle Plugin 2.3.3. Android Studio ftc_app project is already using gradle 3.5 distribution. Robot Controller log has been renamed to /sdcard/RobotControllerLog.txt (note that this change was actually introduced w/ v3.2). Improvements in I2C reliability. Optimized I2C read for REV Expansion Hub, with v1.7 firmware or greater. Updated all external/samples (available through OnBot and in Android project folder). Vuforia Added support for VuMarks that will be used for the 2017-2018 season game. Blocks Update to latest Google Blockly release. Sample op modes can be selected as a template when creating new op mode. Fixed bug where the blocks would disappear temporarily when mouse button is held down. Added blocks for Range.clip and Range.scale. User can now disable/enable Block op modes. Fix to prevent occasional Blocks deadlock. OnBot Java Significant improvements with autocomplete function for OnBot Java editor. Sample op modes can be selected as a template when creating new op mode. Fixes and changes to complete hardware setup feature. Updated (and more useful) onBot welcome message. Known issues: Android Studio After updating to the new v3.3 Android Studio project folder, if you get error messages indicating "InvalidVirtualFileAccessException" then you might need to do a File->Invalidate Caches / Restart to clear the error. OnBot Java Sometimes when you push the build button to build all op modes, the RC returns an error message that the build failed. If you press the build button a second time, the build typically suceeds. Version 3.2 (built on 17.08.02) This version of the software introduces the "OnBot Java" Development Tool. Similar to the FTC Blocks Development Tool, the FTC OnBot Java Development Tool allows a user to create, edit and build op modes dynamically using only a Javascript-enabled web browser. The OnBot Java Development Tool is an integrated development environment (IDE) that is served up by the Robot Controller. Op modes are created and edited using a Javascript-enabled browser (Google Chromse is recommended). Op modes are saved on the Robot Controller Android device directly. The OnBot Java Development Tool provides a Java programming environment that does NOT need Android Studio. Changes with version 3.2 include: Enhanced web-based development tools Introduction of OnBot Java Development Tool. Web-based programming and management features are "always on" (user no longer needs to put Robot Controller into programming mode). Web-based management interface (where user can change Robot Controller name and also easily download Robot Controller log file). OnBot Java, Blocks and Management features available from web based interface. Blocks Programming Development Tool: Changed "LynxI2cColorRangeSensor" block to "REV Color/range sensor" block. Fixed tooltip for ColorSensor.isLightOn block. Added blocks for ColorSensor.getNormalizedColors and LynxI2cColorRangeSensor.getNormalizedColors. Added example op modes for digital touch sensor and REV Robotics Color Distance sensor. User selectable color themes. Includes many minor enhancements and fixes (too numerous to list). Known issues: Auto complete function is incomplete and does not support the following (for now): Access via this keyword Access via super keyword Members of the super cloass, not overridden by the class Any methods provided in the current class Inner classes Can't handle casted objects Any objects coming from an parenthetically enclosed expression Version 3.10 (built on 17.05.09) This version of the software provides support for the REV Robotics Expansion Hub. This version also includes improvements in the USB communication layer in an effort to enhance system resiliency. If you were using a 2.x version of the software previously, updating to version 3.1 requires that you also update your Driver Station software in addition to updating the Robot Controller software. Also note that in version 3.10 software, the setMaxSpeed and getMaxSpeed methods are no longer available (not deprecated, they have been removed from the SDK). Also note that the the new 3.x software incorporates motor profiles that a user can select as he/she configures the robot. Changes include: Blocks changes Added VuforiaTrackableDefaultListener.getPose and Vuforia.trackPose blocks. Added optimized blocks support for Vuforia extended tracking. Added atan2 block to the math category. Added useCompetitionFieldTargetLocations parameter to Vuforia.initialize block. If set to false, the target locations are placed at (0,0,0) with target orientation as specified in https://github.com/gearsincorg/FTCVuforiaDemo/blob/master/Robot_Navigation.java tutorial op mode. Incorporates additional improvements to USB comm layer to improve system resiliency (to recover from a greater number of communication disruptions). Additional Notes Regarding Version 3.00 (built on 17.04.13) In addition to the release changes listed below (see section labeled "Version 3.00 (built on 17.04.013)"), version 3.00 has the following important changes: Version 3.00 software uses a new version of the FTC Robocol (robot protocol). If you upgrade to v3.0 on the Robot Controller and/or Android Studio side, you must also upgrade the Driver Station software to match the new Robocol. Version 3.00 software removes the setMaxSpeed and getMaxSpeed methods from the DcMotor class. If you have an op mode that formerly used these methods, you will need to remove the references/calls to these methods. Instead, v3.0 provides the max speed information through the use of motor profiles that are selected by the user during robot configuration. Version 3.00 software currently does not have a mechanism to disable extra i2c sensors. We hope to re-introduce this function with a release in the near future. Version 3.00 (built on 17.04.13) *** Use this version of the software at YOUR OWN RISK!!! *** This software is being released as an "alpha" version. Use this version at your own risk! This pre-release software contains SIGNIFICANT changes, including changes to the Wi-Fi Direct pairing mechanism, rewrites of the I2C sensor classes, changes to the USB/FTDI layer, and the introduction of support for the REV Robotics Expansion Hub and the REV Robotics color-range-light sensor. These changes were implemented to improve the reliability and resiliency of the FTC control system. Please note, however, that version 3.00 is considered "alpha" code. This code is being released so that the FIRST community will have an opportunity to test the new REV Expansion Hub electronics module when it becomes available in May. The developers do not recommend using this code for critical applications (i.e., competition use). *** Use this version of the software at YOUR OWN RISK!!! *** Changes include: Major rework of sensor-related infrastructure. Includes rewriting sensor classes to implement synchronous I2C communication. Fix to reset Autonomous timer back to 30 seconds. Implementation of specific motor profiles for approved 12V motors (includes Tetrix, AndyMark, Matrix and REV models). Modest improvements to enhance Wi-Fi P2P pairing. Fixes telemetry log addition race. Publishes all the sources (not just a select few). Includes Block programming improvements Addition of optimized Vuforia blocks. Auto scrollbar to projects and sounds pages. Fixed blocks paste bug. Blocks execute after while-opModeIsActive loop (to allow for cleanup before exiting op mode). Added gyro integratedZValue block. Fixes bug with projects page for Firefox browser. Added IsSpeaking block to AndroidTextToSpeech. Implements support for the REV Robotics Expansion Hub Implements support for integral REV IMU (physically installed on I2C bus 0, uses same Bosch BNO055 9 axis absolute orientation sensor as Adafruit 9DOF abs orientation sensor). - Implements support for REV color/range/light sensor. Provides support to update Expansion Hub firmware through FTC SDK. Detects REV firmware version and records in log file. Includes support for REV Control Hub (note that the REV Control Hub is not yet approved for FTC use). Implements FTC Blocks programming support for REV Expansion Hub and sensor hardware. Detects and alerts when I2C device disconnect. Version 2.62 (built on 17.01.07) Added null pointer check before calling modeToByte() in finishModeSwitchIfNecessary method for ModernRoboticsUsbDcMotorController class. Changes to enhance Modern Robotics USB protocol robustness. Version 2.61 (released on 16.12.19) Blocks Programming mode changes: Fix to correct issue when an exception was thrown because an OpticalDistanceSensor object appears twice in the hardware map (the second time as a LightSensor). Version 2.6 (released on 16.12.16) Fixes for Gyro class: Improve (decrease) sensor refresh latency. fix isCalibrating issues. Blocks Programming mode changes: Blocks now ignores a device in the configuration xml if the name is empty. Other devices work in configuration work fine. Version 2.5 (internal release on released on 16.12.13) Blocks Programming mode changes: Added blocks support for AdafruitBNO055IMU. Added Download Op Mode button to FtcBocks.html. Added support for copying blocks in one OpMode and pasting them in an other OpMode. The clipboard content is stored on the phone, so the programming mode server must be running. Modified Utilities section of the toolbox. In Programming Mode, display information about the active connections. Fixed paste location when workspace has been scrolled. Added blocks support for the android Accelerometer. Fixed issue where Blocks Upload Op Mode truncated name at first dot. Added blocks support for Android SoundPool. Added type safety to blocks for Acceleration. Added type safety to blocks for AdafruitBNO055IMU.Parameters. Added type safety to blocks for AnalogInput. Added type safety to blocks for AngularVelocity. Added type safety to blocks for Color. Added type safety to blocks for ColorSensor. Added type safety to blocks for CompassSensor. Added type safety to blocks for CRServo. Added type safety to blocks for DigitalChannel. Added type safety to blocks for ElapsedTime. Added type safety to blocks for Gamepad. Added type safety to blocks for GyroSensor. Added type safety to blocks for IrSeekerSensor. Added type safety to blocks for LED. Added type safety to blocks for LightSensor. Added type safety to blocks for LinearOpMode. Added type safety to blocks for MagneticFlux. Added type safety to blocks for MatrixF. Added type safety to blocks for MrI2cCompassSensor. Added type safety to blocks for MrI2cRangeSensor. Added type safety to blocks for OpticalDistanceSensor. Added type safety to blocks for Orientation. Added type safety to blocks for Position. Added type safety to blocks for Quaternion. Added type safety to blocks for Servo. Added type safety to blocks for ServoController. Added type safety to blocks for Telemetry. Added type safety to blocks for Temperature. Added type safety to blocks for TouchSensor. Added type safety to blocks for UltrasonicSensor. Added type safety to blocks for VectorF. Added type safety to blocks for Velocity. Added type safety to blocks for VoltageSensor. Added type safety to blocks for VuforiaLocalizer.Parameters. Added type safety to blocks for VuforiaTrackable. Added type safety to blocks for VuforiaTrackables. Added type safety to blocks for enums in AdafruitBNO055IMU.Parameters. Added type safety to blocks for AndroidAccelerometer, AndroidGyroscope, AndroidOrientation, and AndroidTextToSpeech. Version 2.4 (released on 16.11.13) Fix to avoid crashing for nonexistent resources. Blocks Programming mode changes: Added blocks to support OpenGLMatrix, MatrixF, and VectorF. Added blocks to support AngleUnit, AxesOrder, AxesReference, CameraDirection, CameraMonitorFeedback, DistanceUnit, and TempUnit. Added blocks to support Acceleration. Added blocks to support LinearOpMode.getRuntime. Added blocks to support MagneticFlux and Position. Fixed typos. Made blocks for ElapsedTime more consistent with other objects. Added blocks to support Quaternion, Velocity, Orientation, AngularVelocity. Added blocks to support VuforiaTrackables, VuforiaTrackable, VuforiaLocalizer, VuforiaTrackableDefaultListener. Fixed a few blocks. Added type checking to new blocks. Updated to latest blockly. Added default variable blocks to navigation and matrix blocks. Fixed toolbox entry for openGLMatrix_rotation_withAxesArgs. When user downloads Blocks-generated op mode, only the .blk file is downloaded. When user uploads Blocks-generated op mode (.blk file), Javascript code is auto generated. Added DbgLog support. Added logging when a blocks file is read/written. Fixed bug to properly render blocks even if missing devices from configuration file. Added support for additional characters (not just alphanumeric) for the block file names (for download and upload). Added support for OpMode flavor (“Autonomous” or “TeleOp”) and group. Changes to Samples to prevent tutorial issues. Incorporated suggested changes from public pull 216 (“Replace .. paths”). Remove Servo Glitches when robot stopped. if user hits “Cancels” when editing a configuration file, clears the unsaved changes and reverts to original unmodified configuration. Added log info to help diagnose why the Robot Controller app was terminated (for example, by watch dog function). Added ability to transfer log from the controller. Fixed inconsistency for AngularVelocity Limit unbounded growth of data for telemetry. If user does not call telemetry.update() for LinearOpMode in a timely manner, data added for telemetry might get lost if size limit is exceeded. Version 2.35 (released on 16.10.06) Blockly programming mode - Removed unnecesary idle() call from blocks for new project. Version 2.30 (released on 16.10.05) Blockly programming mode: Mechanism added to save Blockly op modes from Programming Mode Server onto local device To avoid clutter, blocks are displayed in categorized folders Added support for DigitalChannel Added support for ModernRoboticsI2cCompassSensor Added support for ModernRoboticsI2cRangeSensor Added support for VoltageSensor Added support for AnalogInput Added support for AnalogOutput Fix for CompassSensor setMode block Vuforia Fix deadlock / make camera data available while Vuforia is running. Update to Vuforia 6.0.117 (recommended by Vuforia and Google to close security loophole). Fix for autonomous 30 second timer bug (where timer was in effect, even though it appeared to have timed out). opModeIsActive changes to allow cleanup after op mode is stopped (with enforced 2 second safety timeout). Fix to avoid reading i2c twice. Updated sample Op Modes. Improved logging and fixed intermittent freezing. Added digital I/O sample. Cleaned up device names in sample op modes to be consistent with Pushbot guide. Fix to allow use of IrSeekerSensorV3. Version 2.20 (released on 16.09.08) Support for Modern Robotics Compass Sensor. Support for Modern Robotics Range Sensor. Revise device names for Pushbot templates to match the names used in Pushbot guide. Fixed bug so that IrSeekerSensorV3 device is accessible as IrSeekerSensor in hardwareMap. Modified computer vision code to require an individual Vuforia license (per legal requirement from PTC). Minor fixes. Blockly enhancements: Support for Voltage Sensor. Support for Analog Input. Support for Analog Output. Support for Light Sensor. Support for Servo Controller. Version 2.10 (released on 16.09.03) Support for Adafruit IMU. Improvements to ModernRoboticsI2cGyro class Block on reset of z axis. isCalibrating() returns true while gyro is calibration. Updated sample gyro program. Blockly enhancements support for android.graphics.Color. added support for ElapsedTime. improved look and legibility of blocks. support for compass sensor. support for ultrasonic sensor. support for IrSeeker. support for LED. support for color sensor. support for CRServo prompt user to configure robot before using programming mode. Provides ability to disable audio cues. various bug fixes and improvements. Version 2.00 (released on 16.08.19) This is the new release for the upcoming 2016-2017 FIRST Tech Challenge Season. Channel change is enabled in the FTC Robot Controller app for Moto G 2nd and 3rd Gen phones. Users can now use annotations to register/disable their Op Modes. Changes in the Android SDK, JDK and build tool requirements (minsdk=19, java 1.7, build tools 23.0.3). Standardized units in analog input. Cleaned up code for existing analog sensor classes. setChannelMode and getChannelMode were REMOVED from the DcMotorController class. This is important - we no longer set the motor modes through the motor controller. setMode and getMode were added to the DcMotor class. ContinuousRotationServo class has been added to the FTC SDK. Range.clip() method has been overloaded so it can support this operation for int, short and byte integers. Some changes have been made (new methods added) on how a user can access items from the hardware map. Users can now set the zero power behavior for a DC motor so that the motor will brake or float when power is zero. Prototype Blockly Programming Mode has been added to FTC Robot Controller. Users can place the Robot Controller into this mode, and then use a device (such as a laptop) that has a Javascript enabled browser to write Blockly-based Op Modes directly onto the Robot Controller. Users can now configure the robot remotely through the FTC Driver Station app. Android Studio project supports Android Studio 2.1.x and compile SDK Version 23 (Marshmallow). Vuforia Computer Vision SDK integrated into FTC SDK. Users can use sample vision targets to get localization information on a standard FTC field. Project structure has been reorganized so that there is now a TeamCode package that users can use to place their local/custom Op Modes into this package. Inspection function has been integrated into the FTC Robot Controller and Driver Station Apps (Thanks Team HazMat… 9277 & 10650!). Audio cues have been incorporated into FTC SDK. Swap mechanism added to FTC Robot Controller configuration activity. For example, if you have two motor controllers on a robot, and you misidentified them in your configuration file, you can use the Swap button to swap the devices within the configuration file (so you do not have to manually re-enter in the configuration info for the two devices). Fix mechanism added to all user to replace an electronic module easily. For example, suppose a servo controller dies on your robot. You replace the broken module with a new module, which has a different serial number from the original servo controller. You can use the Fix button to automatically reconfigure your configuration file to use the serial number of the new module. Improvements made to fix resiliency and responsiveness of the system. For LinearOpMode the user now must for a telemetry.update() to update the telemetry data on the driver station. This update() mechanism ensures that the driver station gets the updated data properly and at the same time. The Auto Configure function of the Robot Controller is now template based. If there is a commonly used robot configuration, a template can be created so that the Auto Configure mechanism can be used to quickly configure a robot of this type. The logic to detect a runaway op mode (both in the LinearOpMode and OpMode types) and to abort the run, then auto recover has been improved/implemented. Fix has been incorporated so that Logitech F310 gamepad mappings will be correct for Marshmallow users. Release 16.07.08 For the ftc_app project, the gradle files have been modified to support Android Studio 2.1.x. Release 16.03.30 For the MIT App Inventor, the design blocks have new icons that better represent the function of each design component. Some changes were made to the shutdown logic to ensure the robust shutdown of some of our USB services. A change was made to LinearOpMode so as to allow a given instance to be executed more than once, which is required for the App Inventor. Javadoc improved/updated. Release 16.03.09 Changes made to make the FTC SDK synchronous (significant change!) waitOneFullHardwareCycle() and waitForNextHardwareCycle() are no longer needed and have been deprecated. runOpMode() (for a LinearOpMode) is now decoupled from the system's hardware read/write thread. loop() (for an OpMode) is now decoupled from the system's hardware read/write thread. Methods are synchronous. For example, if you call setMode(DcMotorController.RunMode.RESET_ENCODERS) for a motor, the encoder is guaranteed to be reset when the method call is complete. For legacy module (NXT compatible), user no longer has to toggle between read and write modes when reading from or writing to a legacy device. Changes made to enhance reliability/robustness during ESD event. Changes made to make code thread safe. Debug keystore added so that user-generated robot controller APKs will all use the same signed key (to avoid conflicts if a team has multiple developer laptops for example). Firmware version information for Modern Robotics modules are now logged. Changes made to improve USB comm reliability and robustness. Added support for voltage indicator for legacy (NXT-compatible) motor controllers. Changes made to provide auto stop capabilities for op modes. A LinearOpMode class will stop when the statements in runOpMode() are complete. User does not have to push the stop button on the driver station. If an op mode is stopped by the driver station, but there is a run away/uninterruptible thread persisting, the app will log an error message then force itself to crash to stop the runaway thread. Driver Station UI modified to display lowest measured voltage below current voltage (12V battery). Driver Station UI modified to have color background for current voltage (green=good, yellow=caution, red=danger, extremely low voltage). javadoc improved (edits and additional classes). Added app build time to About activity for driver station and robot controller apps. Display local IP addresses on Driver Station About activity. Added I2cDeviceSynchImpl. Added I2cDeviceSync interface. Added seconds() and milliseconds() to ElapsedTime for clarity. Added getCallbackCount() to I2cDevice. Added missing clearI2cPortActionFlag. Added code to create log messages while waiting for LinearOpMode shutdown. Fix so Wifi Direct Config activity will no longer launch multiple times. Added the ability to specify an alternate i2c address in software for the Modern Robotics gyro. Release 16.02.09 Improved battery checker feature so that voltage values get refreshed regularly (every 250 msec) on Driver Station (DS) user interface. Improved software so that Robot Controller (RC) is much more resilient and “self-healing” to USB disconnects: If user attempts to start/restart RC with one or more module missing, it will display a warning but still start up. When running an op mode, if one or more modules gets disconnected, the RC & DS will display warnings,and robot will keep on working in spite of the missing module(s). If a disconnected module gets physically reconnected the RC will auto detect the module and the user will regain control of the recently connected module. Warning messages are more helpful (identifies the type of module that’s missing plus its USB serial number). Code changes to fix the null gamepad reference when users try to reference the gamepads in the init() portion of their op mode. NXT light sensor output is now properly scaled. Note that teams might have to readjust their light threshold values in their op modes. On DS user interface, gamepad icon for a driver will disappear if the matching gamepad is disconnected or if that gamepad gets designated as a different driver. Robot Protocol (ROBOCOL) version number info is displayed in About screen on RC and DS apps. Incorporated a display filter on pairing screen to filter out devices that don’t use the “-“ format. This filter can be turned off to show all WiFi Direct devices. Updated text in License file. Fixed formatting error in OpticalDistanceSensor.toString(). Fixed issue on with a blank (“”) device name that would disrupt WiFi Direct Pairing. Made a change so that the WiFi info and battery info can be displayed more quickly on the DS upon connecting to RC. Improved javadoc generation. Modified code to make it easier to support language localization in the future. Release 16.01.04 Updated compileSdkVersion for apps Prevent Wifi from entering power saving mode removed unused import from driver station Corrrected "Dead zone" joystick code. LED.getDeviceName and .getConnectionInfo() return null apps check for ROBOCOL_VERSION mismatch Fix for Telemetry also has off-by-one errors in its data string sizing / short size limitations error User telemetry output is sorted. added formatting variants to DbgLog and RobotLog APIs code modified to allow for a long list of op mode names. changes to improve thread safety of RobocolDatagramSocket Fix for "missing hardware leaves robot controller disconnected from driver station" error fix for "fast tapping of Init/Start causes problems" (toast is now only instantiated on UI thread). added some log statements for thread life cycle. moved gamepad reset logic inside of initActiveOpMode() for robustness changes made to mitigate risk of race conditions on public methods. changes to try and flag when WiFi Direct name contains non-printable characters. fix to correct race condition between .run() and .close() in ReadWriteRunnableStandard. updated FTDI driver made ReadWriteRunnableStanard interface public. fixed off-by-one errors in Command constructor moved specific hardware implmentations into their own package. moved specific gamepad implemnatations to the hardware library. changed LICENSE file to new BSD version. fixed race condition when shutting down Modern Robotics USB devices. methods in the ColorSensor classes have been synchronized. corrected isBusy() status to reflect end of motion. corrected "back" button keycode. the notSupported() method of the GyroSensor class was changed to protected (it should not be public). Release 15.11.04.001 Added Support for Modern Robotics Gyro. The GyroSensor class now supports the MR Gyro Sensor. Users can access heading data (about Z axis) Users can also access raw gyro data (X, Y, & Z axes). Example MRGyroTest.java op mode included. Improved error messages More descriptive error messages for exceptions in user code. Updated DcMotor API Enable read mode on new address in setI2cAddress Fix so that driver station app resets the gamepads when switching op modes. USB-related code changes to make USB comm more responsive and to display more explicit error messages. Fix so that USB will recover properly if the USB bus returns garbage data. Fix USB initializtion race condition. Better error reporting during FTDI open. More explicit messages during USB failures. Fixed bug so that USB device is closed if event loop teardown method was not called. Fixed timer UI issue Fixed duplicate name UI bug (Legacy Module configuration). Fixed race condition in EventLoopManager. Fix to keep references stable when updating gamepad. For legacy Matrix motor/servo controllers removed necessity of appending "Motor" and "Servo" to controller names. Updated HT color sensor driver to use constants from ModernRoboticsUsbLegacyModule class. Updated MR color sensor driver to use constants from ModernRoboticsUsbDeviceInterfaceModule class. Correctly handle I2C Address change in all color sensors Updated/cleaned up op modes. Updated comments in LinearI2cAddressChange.java example op mode. Replaced the calls to "setChannelMode" with "setMode" (to match the new of the DcMotor method). Removed K9AutoTime.java op mode. Added MRGyroTest.java op mode (demonstrates how to use MR Gyro Sensor). Added MRRGBExample.java op mode (demonstrates how to use MR Color Sensor). Added HTRGBExample.java op mode (demonstrates how to use HT legacy color sensor). Added MatrixControllerDemo.java (demonstrates how to use legacy Matrix controller). Updated javadoc documentation. Updated release .apk files for Robot Controller and Driver Station apps. Release 15.10.06.002 Added support for Legacy Matrix 9.6V motor/servo controller. Cleaned up build.gradle file. Minor UI and bug fixes for driver station and robot controller apps. Throws error if Ultrasonic sensor (NXT) is not configured for legacy module port 4 or 5. Release 15.08.03.001 New user interfaces for FTC Driver Station and FTC Robot Controller apps. An init() method is added to the OpMode class. For this release, init() is triggered right before the start() method. Eventually, the init() method will be triggered when the user presses an "INIT" button on driver station. The init() and loop() methods are now required (i.e., need to be overridden in the user's op mode). The start() and stop() methods are optional. A new LinearOpMode class is introduced. Teams can use the LinearOpMode mode to create a linear (not event driven) program model. Teams can use blocking statements like Thread.sleep() within a linear op mode. The API for the Legacy Module and Core Device Interface Module have been updated. Support for encoders with the Legacy Module is now working. The hardware loop has been updated for better performance.
molyswu / Hand Detectionusing Neural Networks (SSD) on Tensorflow. This repo documents steps and scripts used to train a hand detector using Tensorflow (Object Detection API). As with any DNN based task, the most expensive (and riskiest) part of the process has to do with finding or creating the right (annotated) dataset. I was interested mainly in detecting hands on a table (egocentric view point). I experimented first with the [Oxford Hands Dataset](http://www.robots.ox.ac.uk/~vgg/data/hands/) (the results were not good). I then tried the [Egohands Dataset](http://vision.soic.indiana.edu/projects/egohands/) which was a much better fit to my requirements. The goal of this repo/post is to demonstrate how neural networks can be applied to the (hard) problem of tracking hands (egocentric and other views). Better still, provide code that can be adapted to other uses cases. If you use this tutorial or models in your research or project, please cite [this](#citing-this-tutorial). Here is the detector in action. <img src="images/hand1.gif" width="33.3%"><img src="images/hand2.gif" width="33.3%"><img src="images/hand3.gif" width="33.3%"> Realtime detection on video stream from a webcam . <img src="images/chess1.gif" width="33.3%"><img src="images/chess2.gif" width="33.3%"><img src="images/chess3.gif" width="33.3%"> Detection on a Youtube video. Both examples above were run on a macbook pro **CPU** (i7, 2.5GHz, 16GB). Some fps numbers are: | FPS | Image Size | Device| Comments| | ------------- | ------------- | ------------- | ------------- | | 21 | 320 * 240 | Macbook pro (i7, 2.5GHz, 16GB) | Run without visualizing results| | 16 | 320 * 240 | Macbook pro (i7, 2.5GHz, 16GB) | Run while visualizing results (image above) | | 11 | 640 * 480 | Macbook pro (i7, 2.5GHz, 16GB) | Run while visualizing results (image above) | > Note: The code in this repo is written and tested with Tensorflow `1.4.0-rc0`. Using a different version may result in [some errors](https://github.com/tensorflow/models/issues/1581). You may need to [generate your own frozen model](https://pythonprogramming.net/testing-custom-object-detector-tensorflow-object-detection-api-tutorial/?completed=/training-custom-objects-tensorflow-object-detection-api-tutorial/) graph using the [model checkpoints](model-checkpoint) in the repo to fit your TF version. **Content of this document** - Motivation - Why Track/Detect hands with Neural Networks - Data preparation and network training in Tensorflow (Dataset, Import, Training) - Training the hand detection Model - Using the Detector to Detect/Track hands - Thoughts on Optimizations. > P.S if you are using or have used the models provided here, feel free to reach out on twitter ([@vykthur](https://twitter.com/vykthur)) and share your work! ## Motivation - Why Track/Detect hands with Neural Networks? There are several existing approaches to tracking hands in the computer vision domain. Incidentally, many of these approaches are rule based (e.g extracting background based on texture and boundary features, distinguishing between hands and background using color histograms and HOG classifiers,) making them not very robust. For example, these algorithms might get confused if the background is unusual or in situations where sharp changes in lighting conditions cause sharp changes in skin color or the tracked object becomes occluded.(see [here for a review](https://www.cse.unr.edu/~bebis/handposerev.pdf) paper on hand pose estimation from the HCI perspective) With sufficiently large datasets, neural networks provide opportunity to train models that perform well and address challenges of existing object tracking/detection algorithms - varied/poor lighting, noisy environments, diverse viewpoints and even occlusion. The main drawbacks to usage for real-time tracking/detection is that they can be complex, are relatively slow compared to tracking-only algorithms and it can be quite expensive to assemble a good dataset. But things are changing with advances in fast neural networks. Furthermore, this entire area of work has been made more approachable by deep learning frameworks (such as the tensorflow object detection api) that simplify the process of training a model for custom object detection. More importantly, the advent of fast neural network models like ssd, faster r-cnn, rfcn (see [here](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md#coco-trained-models-coco-models) ) etc make neural networks an attractive candidate for real-time detection (and tracking) applications. Hopefully, this repo demonstrates this. > If you are not interested in the process of training the detector, you can skip straight to applying the [pretrained model I provide in detecting hands](#detecting-hands). Training a model is a multi-stage process (assembling dataset, cleaning, splitting into training/test partitions and generating an inference graph). While I lightly touch on the details of these parts, there are a few other tutorials cover training a custom object detector using the tensorflow object detection api in more detail[ see [here](https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/) and [here](https://towardsdatascience.com/how-to-train-your-own-object-detector-with-tensorflows-object-detector-api-bec72ecfe1d9) ]. I recommend you walk through those if interested in training a custom object detector from scratch. ## Data preparation and network training in Tensorflow (Dataset, Import, Training) **The Egohands Dataset** The hand detector model is built using data from the [Egohands Dataset](http://vision.soic.indiana.edu/projects/egohands/) dataset. This dataset works well for several reasons. It contains high quality, pixel level annotations (>15000 ground truth labels) where hands are located across 4800 images. All images are captured from an egocentric view (Google glass) across 48 different environments (indoor, outdoor) and activities (playing cards, chess, jenga, solving puzzles etc). <img src="images/egohandstrain.jpg" width="100%"> If you will be using the Egohands dataset, you can cite them as follows: > Bambach, Sven, et al. "Lending a hand: Detecting hands and recognizing activities in complex egocentric interactions." Proceedings of the IEEE International Conference on Computer Vision. 2015. The Egohands dataset (zip file with labelled data) contains 48 folders of locations where video data was collected (100 images per folder). ``` -- LOCATION_X -- frame_1.jpg -- frame_2.jpg ... -- frame_100.jpg -- polygons.mat // contains annotations for all 100 images in current folder -- LOCATION_Y -- frame_1.jpg -- frame_2.jpg ... -- frame_100.jpg -- polygons.mat // contains annotations for all 100 images in current folder ``` **Converting data to Tensorflow Format** Some initial work needs to be done to the Egohands dataset to transform it into the format (`tfrecord`) which Tensorflow needs to train a model. This repo contains `egohands_dataset_clean.py` a script that will help you generate these csv files. - Downloads the egohands datasets - Renames all files to include their directory names to ensure each filename is unique - Splits the dataset into train (80%), test (10%) and eval (10%) folders. - Reads in `polygons.mat` for each folder, generates bounding boxes and visualizes them to ensure correctness (see image above). - Once the script is done running, you should have an images folder containing three folders - train, test and eval. Each of these folders should also contain a csv label document each - `train_labels.csv`, `test_labels.csv` that can be used to generate `tfrecords` Note: While the egohands dataset provides four separate labels for hands (own left, own right, other left, and other right), for my purpose, I am only interested in the general `hand` class and label all training data as `hand`. You can modify the data prep script to generate `tfrecords` that support 4 labels. Next: convert your dataset + csv files to tfrecords. A helpful guide on this can be found [here](https://pythonprogramming.net/creating-tfrecord-files-tensorflow-object-detection-api-tutorial/).For each folder, you should be able to generate `train.record`, `test.record` required in the training process. ## Training the hand detection Model Now that the dataset has been assembled (and your tfrecords), the next task is to train a model based on this. With neural networks, it is possible to use a process called [transfer learning](https://www.tensorflow.org/tutorials/image_retraining) to shorten the amount of time needed to train the entire model. This means we can take an existing model (that has been trained well on a related domain (here image classification) and retrain its final layer(s) to detect hands for us. Sweet!. Given that neural networks sometimes have thousands or millions of parameters that can take weeks or months to train, transfer learning helps shorten training time to possibly hours. Tensorflow does offer a few models (in the tensorflow [model zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md#coco-trained-models-coco-models)) and I chose to use the `ssd_mobilenet_v1_coco` model as my start point given it is currently (one of) the fastest models (read the SSD research [paper here](https://arxiv.org/pdf/1512.02325.pdf)). The training process can be done locally on your CPU machine which may take a while or better on a (cloud) GPU machine (which is what I did). For reference, training on my macbook pro (tensorflow compiled from source to take advantage of the mac's cpu architecture) the maximum speed I got was 5 seconds per step as opposed to the ~0.5 seconds per step I got with a GPU. For reference it would take about 12 days to run 200k steps on my mac (i7, 2.5GHz, 16GB) compared to ~5hrs on a GPU. > **Training on your own images**: Please use the [guide provided by Harrison from pythonprogramming](https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/) on how to generate tfrecords given your label csv files and your images. The guide also covers how to start the training process if training locally. [see [here] (https://pythonprogramming.net/training-custom-objects-tensorflow-object-detection-api-tutorial/)]. If training in the cloud using a service like GCP, see the [guide here](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/running_on_cloud.md). As the training process progresses, the expectation is that total loss (errors) gets reduced to its possible minimum (about a value of 1 or thereabout). By observing the tensorboard graphs for total loss(see image below), it should be possible to get an idea of when the training process is complete (total loss does not decrease with further iterations/steps). I ran my training job for 200k steps (took about 5 hours) and stopped at a total Loss (errors) value of 2.575.(In retrospect, I could have stopped the training at about 50k steps and gotten a similar total loss value). With tensorflow, you can also run an evaluation concurrently that assesses your model to see how well it performs on the test data. A commonly used metric for performance is mean average precision (mAP) which is single number used to summarize the area under the precision-recall curve. mAP is a measure of how well the model generates a bounding box that has at least a 50% overlap with the ground truth bounding box in our test dataset. For the hand detector trained here, the mAP value was **0.9686@0.5IOU**. mAP values range from 0-1, the higher the better. <img src="images/accuracy.jpg" width="100%"> Once training is completed, the trained inference graph (`frozen_inference_graph.pb`) is then exported (see the earlier referenced guides for how to do this) and saved in the `hand_inference_graph` folder. Now its time to do some interesting detection. ## Using the Detector to Detect/Track hands If you have not done this yet, please following the guide on installing [Tensorflow and the Tensorflow object detection api](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md). This will walk you through setting up the tensorflow framework, cloning the tensorflow github repo and a guide on - Load the `frozen_inference_graph.pb` trained on the hands dataset as well as the corresponding label map. In this repo, this is done in the `utils/detector_utils.py` script by the `load_inference_graph` method. ```python detection_graph = tf.Graph() with detection_graph.as_default(): od_graph_def = tf.GraphDef() with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid: serialized_graph = fid.read() od_graph_def.ParseFromString(serialized_graph) tf.import_graph_def(od_graph_def, name='') sess = tf.Session(graph=detection_graph) print("> ====== Hand Inference graph loaded.") ``` - Detect hands. In this repo, this is done in the `utils/detector_utils.py` script by the `detect_objects` method. ```python (boxes, scores, classes, num) = sess.run( [detection_boxes, detection_scores, detection_classes, num_detections], feed_dict={image_tensor: image_np_expanded}) ``` - Visualize detected bounding detection_boxes. In this repo, this is done in the `utils/detector_utils.py` script by the `draw_box_on_image` method. This repo contains two scripts that tie all these steps together. - detect_multi_threaded.py : A threaded implementation for reading camera video input detection and detecting. Takes a set of command line flags to set parameters such as `--display` (visualize detections), image parameters `--width` and `--height`, videe `--source` (0 for camera) etc. - detect_single_threaded.py : Same as above, but single threaded. This script works for video files by setting the video source parameter videe `--source` (path to a video file). ```cmd # load and run detection on video at path "videos/chess.mov" python detect_single_threaded.py --source videos/chess.mov ``` > Update: If you do have errors loading the frozen inference graph in this repo, feel free to generate a new graph that fits your TF version from the model-checkpoint in this repo. Use the [export_inference_graph.py](https://github.com/tensorflow/models/blob/master/research/object_detection/export_inference_graph.py) script provided in the tensorflow object detection api repo. More guidance on this [here](https://pythonprogramming.net/testing-custom-object-detector-tensorflow-object-detection-api-tutorial/?completed=/training-custom-objects-tensorflow-object-detection-api-tutorial/). ## Thoughts on Optimization. A few things that led to noticeable performance increases. - Threading: Turns out that reading images from a webcam is a heavy I/O event and if run on the main application thread can slow down the program. I implemented some good ideas from [Adrian Rosebuck](https://www.pyimagesearch.com/2017/02/06/faster-video-file-fps-with-cv2-videocapture-and-opencv/) on parrallelizing image capture across multiple worker threads. This mostly led to an FPS increase of about 5 points. - For those new to Opencv, images from the `cv2.read()` method return images in [BGR format](https://www.learnopencv.com/why-does-opencv-use-bgr-color-format/). Ensure you convert to RGB before detection (accuracy will be much reduced if you dont). ```python cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB) ``` - Keeping your input image small will increase fps without any significant accuracy drop.(I used about 320 x 240 compared to the 1280 x 720 which my webcam provides). - Model Quantization. Moving from the current 32 bit to 8 bit can achieve up to 4x reduction in memory required to load and store models. One way to further speed up this model is to explore the use of [8-bit fixed point quantization](https://heartbeat.fritz.ai/8-bit-quantization-and-tensorflow-lite-speeding-up-mobile-inference-with-low-precision-a882dfcafbbd). Performance can also be increased by a clever combination of tracking algorithms with the already decent detection and this is something I am still experimenting with. Have ideas for optimizing better, please share! <img src="images/general.jpg" width="100%"> Note: The detector does reflect some limitations associated with the training set. This includes non-egocentric viewpoints, very noisy backgrounds (e.g in a sea of hands) and sometimes skin tone. There is opportunity to improve these with additional data. ## Integrating Multiple DNNs. One way to make things more interesting is to integrate our new knowledge of where "hands" are with other detectors trained to recognize other objects. Unfortunately, while our hand detector can in fact detect hands, it cannot detect other objects (a factor or how it is trained). To create a detector that classifies multiple different objects would mean a long involved process of assembling datasets for each class and a lengthy training process. > Given the above, a potential strategy is to explore structures that allow us **efficiently** interleave output form multiple pretrained models for various object classes and have them detect multiple objects on a single image. An example of this is with my primary use case where I am interested in understanding the position of objects on a table with respect to hands on same table. I am currently doing some work on a threaded application that loads multiple detectors and outputs bounding boxes on a single image. More on this soon.
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Our aggregate liability (including our directors, members, employees and agents), whether in contract, warranty, tort (including negligence, whether active, passive or imputed), product liability, strict liability or other theory, arising out of or relating to the use of NiceHash Platform and Mining Services, or inability to use the Platform and Services under these Terms or under any other document or agreement executed and delivered in connection herewith or contemplated hereby, shall in any event not exceed 100 EUR per user. You will defend, indemnify, and hold NiceHash harmless and all respective employees, officers, directors, and representatives from and against any claims, demand, action, damages, loss, liabilities, costs and expenses (including reasonable attorney fees) arising out of or relating to (i) any third-party claim concerning these Terms, (ii) your use of, or conduct in connection with, NiceHash Platform and Mining Services, (iii) any feedback you provide, (iv) your violation of these Terms, (v) or your violation of any rights of any other person or entity. If you are obligated to indemnify us, we will have the right, in our sole discretion, to control any action or proceeding (at our expense) and determine whether we wish to settle it. If we are obligated to respond to a third-party subpoena or other compulsory legal order or process described above, you will also reimburse us for reasonable attorney fees, as well as our employees’ and contractors’ time and materials spent responding to the third-party subpoena or other compulsory legal order or process at reasonable hourly rates. The Services and the information, products, and services included in or available through the NiceHash Platform may include inaccuracies or typographical errors. Changes are periodically added to the information herein. Improvements or changes on the NiceHash Platform can be made at any time. NICEHASH ACCOUNT The registration of the NiceHash Account is made through the NiceHash Platform, where you are required to enter your email address and password in the registration form. After successful completion of registration, the confirmation email is sent to you. After you confirm your registration by clicking on the link in the confirmation email the NiceHash Account is created. NiceHash will send you proof of completed registration once the process is completed. When you create NiceHash Account, you agree to (i) create a strong password that you change frequently and do not use for any other website, (ii) implement reasonable and appropriate measures designed to secure access to any device which has access to your email address associated with your NiceHash Account and your username and password for your NiceHash Account, (iii) maintain the security of your NiceHash Account by protecting your password and by restricting access to your NiceHash Account; (iv) promptly notify us if you discover or otherwise suspect any security breaches related to your NiceHash Account so we can take all required and possible measures to secure your NiceHash Account and (v) take responsibility for all activities that occur under your NiceHash Account and accept all risks of any authorized or unauthorized access to your NiceHash Account, to the maximum extent permitted by law. Losing access to your email, registered at NiceHash Platform, may also mean losing access to your NiceHash Account. You may not be able to use the NiceHash Platform or Mining Services, execute withdrawals and other security sensitive operations until you regain access to your email address, registered at NiceHash Platform. If you wish to change the email address linked to your NiceHash Account, we may ask you to complete a KYC procedure for security purposes. This step serves solely for the purpose of identification in the process of regaining access to your NiceHash Account. Once the NiceHash Account is created a NiceHash Wallet is automatically created for the NiceHash Account when the request for the first deposit to the NiceHash Wallet is made by the user. Account holder’s NiceHash Wallet is generated by NiceHash Wallet provider. Account holder is strongly suggested to enhance the security of his NiceHash Account by adding an additional security step of Two-factor authentication (hereinafter “2FA”) when logging into his account, withdrawing funds from his NiceHash Wallet or placing a new order. Account holder can enable this security feature in the settings of his NiceHash Account. In the event of losing or changing 2FA code, we may ask the Account holder to complete a KYC procedure for security reasons. This step serves solely for the purpose of identification in the process of reactivating Account holders 2FA and it may be subject to an a In order to use certain functionalities of the NiceHash Platform, such as paying for the acquired hashing power, users must deposit funds to the NiceHash Wallet, as the payments for the hashing power could be made only through NiceHash Wallet. Hashing power providers have two options to get paid for the provided hashing power: (i) by using NiceHash Wallet to receive the payments or (ii) by providing other Bitcoin address where the payments shall be received to. Hashing power providers provide their Bitcoin address to NiceHash by providing such details via Account holder’s profile settings or in a form of a stratum username while connecting to NiceHash stratum servers. Account holder may load funds on his NiceHash Wallet from his Secondary account. Account holder may be charged fees by the Secondary account provider or by the blockchain network for such transaction. NiceHash is not responsible for any fees charged by Secondary account providers or by the blockchain network or for the management and security of the Secondary accounts. Account holder is solely responsible for his use of Secondary accounts and Account holder agrees to comply with all terms and conditions applicable to any Secondary accounts. The timing associated with a load transaction will depend in part upon the performance of Secondary accounts providers, the performance of blockchain network and performance of the NiceHash Wallet provider. NiceHash makes no guarantee regarding the amount of time it may take to load funds on to NiceHash Wallet. NiceHash Wallet shall not be used by Account holders to keep, save and hold funds for longer period and also not for executing other transactions which are not related to the transactions regarding the NiceHash Platform. The NiceHash Wallet shall be used exclusively and only for current and ongoing transactions regarding the NiceHash Platform. Account holders shall promptly withdraw any funds kept on the NiceHash Wallet that will not be used and are not intended for the reasons described earlier. Commission fees may be charged by the NiceHash Wallet provider, by the blockchain network or by NiceHash for any NiceHash Wallet transactions. Please refer to the NiceHash Platform, for more information about the commission fees for NiceHash Wallet transactions which are applicable at the time of the transaction. NiceHash reserves the right to change these commission fees according to the provisions to change these Terms at any time for any reason. You have the right to use the NiceHash Account only in compliance with these Terms and other commercial terms and principles published on the NiceHash Platform. In particular, you must observe all regulations aimed at ensuring the security of funds and financial transactions. Provided that the balance of funds in your NiceHash Wallet is greater than any minimum balance requirements needed to satisfy any of your open orders, you may withdraw from your NiceHash Wallet any amount of funds, up to the total amount of funds in your NiceHash Wallet in excess of such minimum balance requirements, to Secondary Account, less any applicable withdrawal fees charged by NiceHash or by the blockchain network for such transaction. Withdrawals are not processed instantly and may be grouped with other withdrawal requests. Some withdrawals may require additional verification information which you will have to provide in order to process the withdrawal. It may take up to 24 hours before withdrawal is fully processed and distributed to the Blockchain network. Please refer to the NiceHash Platform for more information about the withdrawal fees and withdrawal processing. NiceHash reserves the right to change these fees according to the provisions to change these Terms at any time for any reason. You have the right to close the NiceHash Account. In case you have funds on your NiceHash Wallet you should withdraw funds from your account prior to requesting NiceHash Account closure. After we receive your NiceHash Account closure request we will deactivate your NiceHash Account. You can read more about closing the NiceHash Account in our Privacy Policy. Your NiceHash Account may be deactivated due to your inactivity. Your NiceHash account may be locked and a mandatory KYC procedure is applied for security reasons, if it has been more than 6 month since your last login. NiceHash or any of its partners or affiliates are not responsible for the loss of the funds, stored on or transferred from the NiceHash Wallet, as well as for the erroneous implementation of the transactions made via NiceHash Wallet, where such loss or faulty implementation of the transaction are the result of a malfunction of the NiceHash Wallet and the malfunction was caused by you or the NiceHash Wallet provider. You are obliged to inform NiceHash in case of loss or theft, as well as in the case of any possible misuse of the access data to your NiceHash Account, without any delay, and demand change of access data or closure of your existing NiceHash Account and submit a request for new access data. NiceHash will execute the change of access data or closure of the NiceHash Account and the opening of new NiceHash Account as soon as technically possible and without any undue delay. All information pertaining to registration, including a registration form, generation of NiceHash Wallet and detailed instructions on the use of the NiceHash Account and NiceHash Wallet are available at NiceHash Platform. The registration form as well as the entire system is properly protected from unwanted interference by third parties. KYC PROCEDURE NiceHash is appropriately implementing AML/CTF and security measures to diligently detect and prevent any malicious or unlawful use of NiceHash Services or use, which is strictly prohibited by these Terms, which are deemed as your agreement to provide required personal information for identity verification. Security measures include a KYC procedure, which is aimed at determining the identity of an individual user or an organisation. We may ask you to complete this procedure before enabling some or all functionalities of the NiceHash platform and provide its services. A KYC procedure might be applied as a security measure when: changing the email address linked to your NiceHash Account, losing or changing your 2FA code; logging in to your NiceHash Account for the first time after the launch of the new NiceHash Platform in August 2019, gaining access to all or a portion of NiceHash Services, NiceHash Wallet and its related services or any portion thereof if they were disabled due to and activating your NiceHash Account if it has been deactivated due to its inactivity and/or security or other reasons. HASHING POWER TRANSACTIONS General NiceHash may, at any time and in our sole discretion, (i) refuse any order submitted or provided hashing power, (ii) cancel an order or part of the order before it is executed, (iii) impose limits on the order amount permitted or on provided hashing power or (iv) impose any other conditions or restrictions upon your use of the NiceHash Platform and Mining Services without prior notice. For example, but not limited to, NiceHash may limit the number of open orders that you may establish or limit the type of supported Hashing power rigs and mining algorithms or NiceHash may restrict submitting orders or providing hashing power from certain locations. Please refer to the NiceHash Platform, for more information about terminology, hashing power transactions’ definitions and descriptions, order types, order submission, order procedure, order rules and other restrictions and limitations of the hashing power transactions. NiceHash reserves the right to change any transaction, definitions, description, order types, procedure, rules, restrictions and limitations at any time for any reason. Orders, provision of hashing power, payments, deposits, withdrawals and other transactions are accepted only through the interface of the NiceHash Platform, NiceHash API and NiceHash Account and are fixed by the software and hardware tools of the NiceHash Platform. If you do not understand the meaning of any transaction option, NiceHash strongly encourages you not to utilize any of those options. Hashing Power Order In order to submit an Hashing Power Order via the NiceHash Account, the Hashing power buyer must have available funds in his NiceHash Wallet. Hashing power buyer submits a new order to buy hashing power via the NiceHash Platform or via the NiceHash API by setting the following parameters in the order form: NiceHash service server location, third-party mining pool, algorithm to use, order type, set amount he is willing to spend on this order, set price per hash he is willing to pay, optionally approximate limit maximum hashing power for his order and other parameters as requested and by confirming his order. Hashing power buyer may submit an order in maximum amount of funds available on his NiceHash Wallet at the time of order submission. Order run time is only approximate since order’s lifetime is based on the number of hashes that it delivers. Particularly during periods of high volume, illiquidity, fast movement or volatility in the marketplace for any digital assets or hashing power, the actual price per hash at which some of the orders are executed may be different from the prevailing price indicated on NiceHash Platform at the time of your order. You understand that NiceHash is not liable for any such price fluctuations. In the event of market disruption, NiceHash Services disruption, NiceHash Hashing Power Marketplace disruption or manipulation or Force Majeure Event, NiceHash may do one or more of the following: (i) suspend access to the NiceHash Account or NiceHash Platform, or (ii) prevent you from completing any actions in the NiceHash Account, including closing any open orders. Following any such event, when trading resumes, you acknowledge that prevailing market prices may differ significantly from the prices available prior to such event. When Hashing power buyer submits an order for purchasing of the Hashing power via NiceHash Platform or via the NiceHash API he authorizes NiceHash to execute the order on his behalf and for his account in accordance with such order. Hashing power buyer acknowledges and agrees that NiceHash is not acting as his broker, intermediary, agent or advisor or in any fiduciary capacity. NiceHash executes the order in set order amount minus NiceHash’s processing fee. Once the order is successfully submitted the order amount starts to decrease in real time according to the payments for the provided hashing power. Hashing power buyer agrees to pay applicable processing fee to NiceHash for provided services. The NiceHash’s fees are deducted from Hashing power buyer’s NiceHash Wallet once the whole order is exhausted and completed. Please refer to the NiceHash Platform, for more information about the fees which are applicable at the time of provision of services. NiceHash reserves the right to change these fees according to the provisions to change these Terms at any time for any reason. The changed fees will apply only for the NiceHash Services provided after the change of the fees. All orders submitted prior the fee change but not necessary completed prior the fee change will be charged according to the fees applicable at the time of the submission of the order. NiceHash will attempt, on a commercially reasonable basis, to execute the Hashing power buyer’s purchase of the hashing power on the Hashing power marketplace under these Terms according to the best-effort delivery approach. In this respect NiceHash does not guarantee that the hashing power will actually be delivered or verified and does not guarantee any quality of the NiceHash Services. Hashing power buyer may cancel a submitted order during order’s lifetime. If an order has been partially executed, Hashing power buyer may cancel the unexecuted remainder of the order. In this case the NiceHash’s processing fee will apply only for the partially executed order. NiceHash reserves the right to refuse any order cancellation request once the order has been submitted. Selling Hashing Power and the Provision of Hashing Power In order to submit the hashing power to the NiceHash stratum server the Hashing power provider must first point its Hashing power rig to the NiceHash stratum server. Hashing power provider is solely responsible for configuration of his Hashing power rig. The Hashing power provider gets paid by Hashing power buyers for all validated and accepted work that his Hashing power rig has produced. The provided hashing power is validated by NiceHash’s stratum engine and validator. Once the hashing power is validated the Hashing power provider is entitled to receive the payment for his work. NiceHash logs all validated hashing power which was submitted by the Hashing power provider. The Hashing power provider receives the payments of current globally weighted average price on to his NiceHash Wallet or his selected personal Bitcoin address. The payments are made periodically depending on the height of payments. NiceHash reserves the right to hold the payments any time and for any reason by indicating the reason, especially if the payments represent smaller values. Please refer to the NiceHash Platform, for more information about the height of payments for provided hashing power, how the current globally weighted average price is calculated, payment periods, payment conditions and conditions for detention of payments. NiceHash reserves the right to change this payment policy according to the provisions to change these Terms at any time for any reason. All Hashing power rig’s earnings and profitability calculations on NiceHash Platform are only for informational purposes. NiceHash does not warrant that your Hashing power rigs would achieve the same profitability or earnings as calculated on NiceHash Platform. You hereby acknowledge that it is possible that your Hashing power rigs would not be as profitable as indicated in our informational calculations or would not be profitable at all. Hashing power provider agrees to pay applicable processing fee to NiceHash for provided Services. The NiceHash’s fees are deducted from all the payments made to the Hashing power provider for his provided work. Please refer to the NiceHash Platform, for more information about the fees which are applicable at the time of provision of services. Hashing power provider which has not submitted any hashing power to the NiceHash stratum server for a period of 90 days agrees that a processing fee of 0.00001000 BTC or less, depending on the unpaid mining balance, will be deducted from his unpaid mining balance. NiceHash reserves the right to change these fees according to the provisions to change these Terms at any time for any reason. The changed fees will apply only for the NiceHash Services provided after the change of the fees. NiceHash will attempt, on a commercially reasonable basis, to execute the provision of Hashing power providers’ hashing power on the Hashing power marketplace under these Terms according to the best-effort delivery approach. In this respect NiceHash does not guarantee that the hashing power will actually be delivered or verified and does not guarantee any quality of the NiceHash Services. Hashing power provider may disconnect the Hashing power rig from the NiceHash stratum server any time. NiceHash reserves the right to refuse any Hashing power rig once the Hashing power rig has been pointed towards NiceHash stratum server. RESTRICTIONS When accessing the NiceHash Platform or using the Mining Services or NiceHash Wallet, you warrant and agree that you: will not use the Services for any purpose that is unlawful or prohibited by these Terms, will not violate any law, contract, intellectual property or other third-party right or commit a tort, are solely responsible for your conduct while accessing the NiceHash Platform or using the Mining Services or NiceHash Wallet, will not access the NiceHash Platform or use the Mining Services in any manner that could damage, disable, overburden, or impair the provision of the Services or interfere with any other party's use and enjoyment of the Services, will not misuse and/or maliciously use Hashing power rigs, you will particularly refrain from using network botnets or using NiceHash Platform or Mining Services with Hashing power rigs without the knowledge or awareness of Hashing power rig owner(s), will not perform or attempt to perform any kind of malicious attacks on blockchains with the use of the NiceHash Platform or Mining Services, intended to maliciously gain control of more than 50% of the network's mining hash rate, will not use the NiceHash Platform or Mining Services for any kind of market manipulation or disruption, such as but not limited to NiceHash Mining Services disruption and NiceHash Hashing Power Marketplace manipulation. In case of any of the above mentioned events, NiceHash reserves the right to immediately suspend your NiceHash Account, freeze or block the funds in the NiceHash Wallet, and suspend your access to NiceHash Platform, particularly if NiceHash believes that such NiceHash Account are in violation of these Terms or Privacy Policy, or any applicable laws and regulation. RIGHTS AND OBLIGATIONS In the event of disputes with you, NiceHash is obliged to prove that the NiceHash service which is the subject of the dispute was not influenced by technical or other failure. You will have possibility to check at any time, subject to technical availability, the transactions details, statistics and available balance of the funds held on the NiceHash Wallet, through access to the NiceHash Account. You may not obtain or attempt to obtain any materials or information through any means not intentionally made available or provided to you or public through the NiceHash Platform or Mining Services. We may, in our sole discretion, at any time, for any or no reason and without liability to you, with prior notice (i) terminate all rights and obligations between you and NiceHash derived from these Terms, (ii) suspend your access to all or a portion of NiceHash Services, NiceHash Wallet and its related services or any portion thereof and delete or deactivate your NiceHash Account and all related information and files in such account (iii) modify, suspend or discontinue, temporarily or permanently, any portion of NiceHash Platform or (iv) provide enhancements or improvements to the features and functionality of the NiceHash Platform, which may include patches, bug fixes, updates, upgrades and other modifications. Any such change may modify or delete certain portion, features or functionalities of the NiceHash Services. You agree that NiceHash has no obligation to (i) provide any updates, or (ii) continue to provide or enable any particular portion, features or functionalities of the NiceHash Services to you. You further agree that all changes will be (i) deemed to constitute an integral part of the NiceHash Platform, and (ii) subject to these Terms. In the event of your breach of these Terms, including but not limited to, for instance, in the event that you breach any term of these Terms, due to legal grounds originating in anti-money laundering and know your client regulation and procedures, or any other relevant applicable regulation, all right and obligations between you and NiceHash derived from these Terms terminate automatically if you fail to comply with these Terms within the notice period of 8 days after you have been warned by NiceHash about the breach and given 8 days period to cure the breaches. NiceHash reserves the right to keep these rights and obligations in force despite your breach of these Terms. In the event of termination, NiceHash will attempt to return you any funds stored on your NiceHash Wallet not otherwise owed to NiceHash, unless NiceHash believes you have committed fraud, negligence or other misconduct. You acknowledge that the NiceHash Services and NiceHash Wallet may be suspended for maintenance. Technical information about the hashing power transactions, including information about chosen server locations, algorithms used, selected mining pools, your business or activities, including all financial and technical information, specifications, technology together with all details of prices, current transaction performance and future business strategy represent confidential information and trade secrets. NiceHash shall, preserve the confidentiality of all before mentioned information and shall not disclose or cause or permit to be disclosed without your permission any of these information to any person save to the extent that such disclosure is strictly to enable you to perform or comply with any of your obligations under these Terms, or to the extent that there is an irresistible legal requirement on you or NiceHash to do so; or where the information has come into the public domain otherwise than through a breach of any of the terms of these Terms. NiceHash shall not be entitled to make use of any of these confidential information and trade secrets other than during the continuance of and pursuant to these Terms and then only for the purpose of carrying out its obligations pursuant to these Terms. NICEHASH MINER LICENSE (NICEHASH MINING SOFTWARE LICENSE) NiceHash Mining Software whether on disk, in read only memory, or any other media or in any other form is licensed, not sold, to you by NiceHash for use only under these Terms. NiceHash retains ownership of the NiceHash Mining Software itself and reserves all rights not expressly granted to you. Subject to these Terms, you are granted a limited, non-transferable, non-exclusive and a revocable license to download, install and use the NiceHash Mining Software. You may not distribute or make the NiceHash Mining Software available over a network where it could be used by multiple devices at the same time. You may not rent, lease, lend, sell, redistribute, assign, sublicense host, outsource, disclose or otherwise commercially exploit the NiceHash Mining Software or make it available to any third party. There is no license fee for the NiceHash Mining Software. NiceHash reserves the right to change the license fee policy according to the provisions to change these Terms any time and for any reason, including to decide to start charging the license fee for the NiceHash Mining Software. You are responsible for any and all applicable taxes. You may not, and you agree not to or enable others to, copy, decompile, reverse engineer, reverse compile, disassemble, attempt to derive the source code of, decrypt, modify, or create derivative works of the NiceHash Mining Software or any services provided by the NiceHash Mining Software, or any part thereof (except as and only to the extent any foregoing restriction is prohibited by applicable law or to the extent as may be permitted by the licensing terms governing use of open-sourced components included with the NiceHash Mining Software). If you choose to allow automatic updates, your device will periodically check with NiceHash for updates and upgrades to the NiceHash Mining Software and, if an update or upgrade is available, the update or upgrade will automatically download and install onto your device and, if applicable, your peripheral devices. You can turn off the automatic updates altogether at any time by changing the automatic updates settings found within the NiceHash Mining Software. You agree that NiceHash may collect and use technical and related information, including but not limited to technical information about your computer, system and application software, and peripherals, that is gathered periodically to facilitate the provision of software updates, product support and other services to you (if any) related to the NiceHash Mining Software and to verify compliance with these Terms. NiceHash may use this information, as long as it is in a form that does not personally identify you, to improve our NiceHash Services. NiceHash Mining Software contains features that rely upon information about your selected mining pools. You agree to our transmission, collection, maintenance, processing, and use of all information obtained from you about your selected mining pools. You can opt out at any time by going to settings in the NiceHash Mining Software. NiceHash may provide interest-based advertising to you. If you do not want to receive relevant ads in the NiceHash Mining Software, you can opt out at any time by going to settings in the NiceHash Mining Software. If you opt out, you will continue to receive the same number of ads, but they may be less relevant because they will not be based on your interest. NiceHash Mining Software license is effective until terminated. All provisions of these Terms regarding the termination apply also for the NiceHash Mining Software license. Upon the termination of NiceHash Mining Software license, you shall cease all use of the NiceHash Mining Software and destroy or delete all copies, full or partial, of the NiceHash Mining Software. THIRD PARTY MINERS AND PLUGINS Third Party Miners and Plugins are a third party software which enables the best and most efficient mining operations. NiceHash Miner integrates third party mining software using a third party miner plugin system. Third Party Mining Software is a closed source software which supports mining algorithms for cryptocurrencies and can be integrated into NiceHash Mining Software. Third Party Miner Plugin enables the connection between NiceHash Mining Software and Third Party Mining Software and it can be closed, as well as open sourced. NiceHash Mining Software user interface enables the user to manually select which available Third Party Miners and Plugins will be downloaded and integrated. Users can select or deselect Third Party Miners and Plugins found in the Plugin Manager window. Some of the available Third Party Miners and Plugins which are most common are preselected by NiceHash, but can be deselected, depending on users' needs. The details of the Third Party Miners and Plugins available for NiceHash Mining Software are accessible within the NiceHash Mining Software user interface. The details include, but not limited to, the author of the software and applicable license information, if applicable information about developer fee for Third Party Miners, software version etc. Developer fees may apply to the use of Third Party Miners and Plugins. NiceHash will not be liable, to the maximum extent permitted by applicable law, for any damages of any kind, including, but not limited to, direct, consequential, incidental, special or indirect damages, arising out of using Third Party Miners and Plugins. The latter includes, but is not limited to: i) any power outages, maintenance, defects, system failures, mistakes, omissions, errors, defects, viruses, delays in operation or transmission or any failure of performance; ii) any unauthorized access, alteration, deletion, destruction, damage, loss or failure to store any data, including records, private key or other credentials, associated with usage of Third Party Miners and Plugins and ii) Force Majeure Event, communications failure, theft or other interruptions. If you choose to allow automatic updates, your device will periodically check with NiceHash for updates and upgrades to the installed Third Party Miners and Plugins, if an update or upgrade is available, the update or upgrade will automatically download and install onto your device and, if applicable, your peripheral devices. You can turn off the automatic updates altogether at any time by changing the automatic updates settings found within the NiceHash Mining Software. NICEHASH QUICKMINER NiceHash QuickMiner is a software application that allows the visitors of the NiceHash Quick Miner web page, accessible athttps://www.nicehash.com/quick-miner, to connect their PC or a mining rig to the NiceHash Hashing Power Marketplace. Visitors of the NiceHash Quick Miner web page can try out and experience crypto currency mining without having to register on the NiceHash Platform and create a NiceHash Account. Users are encouraged to do so as soon as possible in order to collect the funds earned using NiceHash Quick Miner. Users can download NiceHash QuickMiner free of charge. In order to operate NiceHash QuickMiner software needs to automatically detect technical information about users' computer hardware. You agree that NiceHash may collect and use technical and related information. For more information please refer to NiceHash Privacy Policy. Funds arising from the usage of NiceHash QuickMiner are transferred to a dedicated cryptocurrency wallet owned and managed by NiceHash. NiceHash QuickMiner Users expressly agree and acknowledge that completing the registration process and creating a NiceHash Account is necessary in order to collect the funds arising from the usage of NiceHash QuickMiner. Users of NiceHash QuickMiner who do not successfully register a NiceHash Account will lose their right to claim funds arising from their usage of NiceHash QuickMiner. Those funds, in addition to the condition that the user has not been active on the NiceHash QuickMiner web page for consecutive 7 days, will be donated to the charity of choice. NICEHASH PRIVATE ENDPOINT NiceHash Private Endpoint is a network interface that connects users privately and securely to NiceHash Stratum servers. Private Endpoint uses a private IP address and avoids additional latency caused by DDOS protection. All NiceHash Private Mining Proxy servers are managed by NiceHash and kept up-to-date. Users can request a dedicated private access endpoint by filling in the form for NiceHash Private Endpoint Solution available at the NiceHash Platform. In the form the user specifies the email address, country, number of connections and locations and algorithms used. Based on the request NiceHash prepares an individualized offer based on the pricing stipulated on the NiceHash Platform, available at https://www.nicehash.com/private-endpoint-solution. NiceHash may request additional information from the users of the Private Endpoint Solution in order to determine whether we are obligated to collect VAT from you, including your VAT identification number. INTELLECTUAL PROPERTY NiceHash retains all copyright and other intellectual property rights, including inventions, discoveries, knowhow, processes, marks, methods, compositions, formulae, techniques, information and data, whether or not patentable, copyrightable or protectable in trademark, and any trademarks, copyrights or patents based thereon over all content and other materials contained on NiceHash Platform or provided in connection with the Services, including, without limitation, the NiceHash logo and all designs, text, graphics, pictures, information, data, software, source code, as well as the compilation thereof, sound files, other files and the selection and arrangement thereof. This material is protected by international copyright laws and other intellectual property right laws, namely trademark. These Terms shall not be understood and interpreted in a way that they would mean assignment of copyright or other intellectual property rights, unless it is explicitly defined so in these Terms. NiceHash hereby grants you a limited, nonexclusive and non-sublicensable license to access and use NiceHash’s copyrighted work and other intellectual property for your personal or internal business use. Such license is subject to these Terms and does not permit any resale, the distribution, public performance or public display, modifying or otherwise making any derivative uses, use, publishing, transmission, reverse engineering, participation in the transfer or sale, or any way exploit any of the copyrighted work and other intellectual property other than for their intended purposes. This granted license will automatically terminate if NiceHash suspends or terminates your access to the Services, NiceHash Wallet or closes your NiceHash Account. NiceHash will own exclusive rights, including all intellectual property rights, to any feedback including, but not limited to, suggestions, ideas or other information or materials regarding NiceHash Services or related products that you provide, whether by email, posting through our NiceHash Platform, NiceHash Account or otherwise and you irrevocably assign any and all intellectual property rights on such feedback unlimited in time, scope and territory. Any Feedback you submit is non-confidential and shall become the sole property of NiceHash. NiceHash will be entitled to the unrestricted use, modification or dissemination of such feedback for any purpose, commercial or otherwise, without acknowledgment or compensation to you. You waive any rights you may have to the feedback. We have the right to remove any posting you make on NiceHash Platform if, in our opinion, your post does not comply with the content standards defined by these Terms. PRIVACY POLICY Please refer to our NiceHash Platform and Mining Services Privacy Policy published on the NiceHash Platform for information about how we collect, use and share your information, as well as what options do you have with regards to your personal information. COMMUNICATION AND SUPPORT You agree and consent to receive electronically all communications, agreements, documents, receipts, notices and disclosures that NiceHash provides in connection with your NiceHash Account or use of the NiceHash Platform and Services. You agree that NiceHash may provide these communications to you by posting them via the NiceHash Account or by emailing them to you at the email address you provide. You should maintain copies of electronic communications by printing a paper copy or saving an electronic copy. It is your responsibility to keep your email address updated in the NiceHash Account so that NiceHash can communicate with you electronically. You understand and agree that if NiceHash sends you an electronic communication but you do not receive it because your email address is incorrect, out of date, blocked by your service provider, or you are otherwise unable to receive electronic communications, it will be deemed that you have been provided with the communication. You can update your NiceHash Account preferences at any time by logging into your NiceHash Account. If your email address becomes invalid such that electronic communications sent to you by NiceHash are returned, NiceHash may deem your account to be inactive and close it. You may give NiceHash a notice under these Terms by sending an email to support@nicehash.com or contact NiceHash through support located on the NiceHash Platform. All communication and notices pursuant to these Terms must be given in English language. FEES Please refer to the NiceHash Platform for more information about the fees or administrative costs which are applicable at the time of provision of services. NiceHash reserves the right to change these fees according to the provisions to change these Terms at any time for any reason. The changed fees will apply only for the Services provided after the change of the fees. You authorize us, or our designated payment processor, to charge or deduct your NiceHash Account for any applicable fees in connection with the transactions completed via the Services. TAX It is your responsibility to determine what, if any, taxes apply to the transactions you complete or services you provide via the NiceHash Platform, Mining Services and NiceHash Wallet, it is your responsibility to report and remit the correct tax to the appropriate tax authority and all your factual and potential tax obligations are your concern. You agree that NiceHash is not in any case and under no conditions responsible for determining whether taxes apply to your transactions or services or for collecting, reporting, withholding or remitting any taxes arising from any transactions or services. You also agree that NiceHash is not in any case and under no conditions bound to compensate for your tax obligation or give you any advice related to tax issues. All fees and charges payable by you to NiceHash are exclusive of any taxes, and shall certain taxes be applicable, they shall be added on top of the payable amounts. Upon our request, you will provide to us any information that we reasonably request to determine whether we are obligated to collect VAT from you, including your VAT identification number. If any deduction or withholding is required by law, you will notify NiceHash and will pay NiceHash any additional amounts necessary to ensure that the net amount received by NiceHash, after any deduction and withholding, equals the amount NiceHash would have received if no deduction or withholding had been required. Additionally, you will provide NiceHash with documentation showing that the withheld and deducted amounts have been paid to the relevant taxing authority. FINAL PROVISIONS Natural persons and legal entities that are not capable of holding legal rights and obligations are not allowed to create NiceHash Account and use NiceHash Platform or other related services. If NiceHash becomes aware that such natural person or legal entity has created the NiceHash Account or has used NiceHash Services, NiceHash will delete such NiceHash Account and disable any Services and block access to NiceHash Account and NiceHash Services to such natural person or legal entity. If you register to use the NiceHash Services on behalf of a legal entity, you represent and warrant that (i) such legal entity is duly organized and validly existing under the applicable laws of the jurisdiction of its organization; and (ii) you are duly authorized by such legal entity to act on its behalf. These Terms do not create any third-party beneficiary rights in any individual or entity. These Terms forms the entire agreement and understanding relating to the subject matter hereof and supersede any previous and contemporaneous agreements, arrangements or understandings relating to the subject matter hereof to the exclusion of any terms implied by law that may be excluded by contract. If at any time any provision of these Terms is or becomes illegal, invalid or unenforceable, the legality, validity and enforceability of every other provisions will not in any way be impaired. Such illegal, invalid or unenforceable provision of these Terms shall be deemed to be modified and replaced by such legal, valid and enforceable provision or arrangement, which corresponds as closely as possible to our and your will and business purpose pursued and reflected in these Terms. Headings of sections are for convenience only and shall not be used to limit or construe such sections. No failure to enforce nor delay in enforcing, on our side to the Terms, any right or legal remedy shall function as a waiver thereof, nor shall any individual or partial exercise of any right or legal remedy prevent any further or other enforcement of these rights or legal remedies or the enforcement of any other rights or legal remedies. NiceHash reserves the right to make changes, amendments, supplementations or modifications from time to time to these Terms including but not limited to changes of licence agreement for NiceHash Mining Software and of any fees and compensations policies, in its sole discretion and for any reason. We suggest that you review these Terms periodically for changes. If we make changes to these Terms, we will provide you with notice of such changes, such as by sending an email, providing notice on the NiceHash Platform, placing a popup window after login to the NiceHash Account or by posting the amended Terms on the NiceHash Platform and updating the date at the top of these Terms. The amended Terms will be deemed effective immediately upon posting for any new users of the NiceHash Services. In all other cases, the amended Terms will become effective for preexisting users upon the earlier of either: (i) the date users click or press a button to accept such changes in their NiceHash Account, or (ii) continued use of NiceHash Services 30 days after NiceHash provides notice of such changes. Any amended Terms will apply prospectively to use of the NiceHash Services after such changes become effective. The notice of change of these Terms is considered as notice of termination of all rights and obligations between you and NiceHash derived from these Terms with notice period of 30 days, if you do not accept the amended Terms. If you do not agree to any amended Terms, (i) the agreement between you and NiceHash is terminated by expiry of 30 days period which starts after NiceHash provides you a notice of change of these Terms, (ii) you must discontinue using NiceHash Services and (iii) you must inform us regarding your disagreement with the changes and request closure of your NiceHash Account. If you do not inform us regarding your disagreement and do not request closure of you NiceHash Account, we will deem that you agree with the changed Terms. You may not assign or transfer your rights or obligations under these Terms without the prior written consent of NiceHash. NiceHash may assign or transfer any or all of its rights under these Terms, in whole or in part, without obtaining your consent or approval. These Terms shall be governed by and construed and enforced in accordance with the Laws of the British Virgin Islands, and shall be interpreted in all respects as a British Virgin Islands contract. Any transaction, dispute, controversy, claim or action arising from or related to your access or use of the NiceHash Platform or these Terms of Service likewise shall be governed by the Laws of the British Virgin Islands, exclusive of choice-of-law principles. The rights and remedies conferred on NiceHash by, or pursuant to, these Terms are cumulative and are in addition, and without prejudice, to all other rights and remedies otherwise available to NiceHash at law. NiceHash may transfer its rights and obligations under these Terms to other entities which include, but are not limited to H-BIT, d.o.o. and NICEX Ltd, or any other firm or business entity that directly or indirectly acquires all or substantially all of the assets or business of NICEHASH Ltd. If you do not consent to any transfer, you may terminate this agreement and close your NiceHash Account. These Terms are not boilerplate. If you disagree with any of them, believe that any should not apply to you, or wish to negotiate these Terms, please contact NiceHash and immediately navigate away from the NiceHash Platform. Do not use the NiceHash Mining Services, NiceHash Wallet or other related services until you and NiceHash have agreed upon new terms of service. Last updated: March 1, 2021
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