17 skills found
alexeygrigorev / Clothing DatasetClosing dataset, all classes
seralexger / Clothing Detection DatasetClothing detection dataset
youngLBW / CRHD 3KThe first high-definition cloth retouching dataset CRHD-3K.
audio-captioning / Clotho DatasetPython code for handling the Clotho dataset.
seralexger / Clothing Detection Ecommerce DatasetClothing detection dataset
alexeygrigorev / Clothing Dataset SmallClothing dataset, 10 classes
lstearns86 / Clothing Pattern DatasetA large dataset containing images of clothing patterns
dev-you-need / Clothes DatasetDataset of clothes for metric learning tasks and not only for this.
SEmohamedAhmed / LSD VTONAn e-commerce website that has a set of clothes to do try-on using test dataset, and also provides the user to do try-on given they personal and cloth images.
tlpss / ARTF Clothes DatasetCoco-formatted cloth dataset in household settings. The dataset contains about 2000 images of 4 cloth categories.
Bouguedra-Adem / Spot The Mask Challenge By ZindiWeekendzFace masks have become a common public sight in the last few months. The Centers for Disease Control (CDC) recently advised the use of simple cloth face coverings to slow the spread of the virus and help people who may have the virus and do not know it from transmitting it to others. Wearing masks is broadly recognised as critical to reducing community transmission and limiting touching of the face. In a time of concerns about slowing the transmission of COVID-19, increased surveillance combined with AI solutions can improve monitoring and reduce the human effort needed to limit the spread of this disease. The objective of this challenge is to create an image classification machine learning model to accurately predict the likelihood that an image contains a person wearing a face mask, or not. The total dataset contains 1,800+ images of people either wearing masks or not. Your machine learning solution will help policymakers, law enforcement, hospitals, and even commercial businesses ensure that masks are being worn appropriately in public. These solutions can help in the battle to reduce community transmission of COVID-19.
obss / Disgem[EMNLP 2024] Official Implementation of DisGeM: Distractor Generation for Multiple Choice Question with Span Masking
LinlyAC / CCGReIDCloth-changing group re-identification dataset (TPAMI 2024)
dustin-nguyen-qil / Lifelong CC ReIDRe-implementation of existing Lifelong Re-ID methods with evaluation on cloth-changing Re-ID datasets.
vijaykrishnavanshi / Fashion Mnist AppA Flask app to serve a keras model trained over Fashion MNIST Dataset. Takes image as an input and outputs the category of cloth recognised in the uploaded image by the neural network.
neha13rana / Cloth Recommendation SystemWe have chosen a fashion dataset for our system. We've created a clothing recommendation system using data mining and content-based filtering concepts. Customers can input a cloth ID and receive details on the top 5 related clothing items.
Abhik35 / Assignment Decision Tree Company DataAssignment About the data: Let’s consider a Company dataset with around 10 variables and 400 records. The attributes are as follows: Sales -- Unit sales (in thousands) at each location Competitor Price -- Price charged by competitor at each location Income -- Community income level (in thousands of dollars) Advertising -- Local advertising budget for company at each location (in thousands of dollars) Population -- Population size in region (in thousands) Price -- Price company charges for car seats at each site Shelf Location at stores -- A factor with levels Bad, Good and Medium indicating the quality of the shelving location for the car seats at each site Age -- Average age of the local population Education -- Education level at each location Urban -- A factor with levels No and Yes to indicate whether the store is in an urban or rural location US -- A factor with levels No and Yes to indicate whether the store is in the US or not The company dataset looks like this: Problem Statement: A cloth manufacturing company is interested to know about the segment or attributes causes high sale. Approach - A decision tree can be built with target variable Sale (we will first convert it in categorical variable) & all other variable will be independent in the analysis.
