Photos management

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

From Python basics to Machine Learning and PyTorch Deep Learning - one day at a time, explore it all

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

The CGI2Real_Multi-Class_Image_Classifier categorizes humans, horses, or both using transfer learning from Inception CNN. Trained on synthetic images, it can also classify real ones.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

⚡ This project utilizes Convolutional Neural Networks (CNNs) to develop a robust image classification model capable of accurately identifying hand gestures representing rock, paper, and scissors.

⚡ This repository implements CNN model using TensorFlow to classify images of shoes, sandals, and boots. The project provides a comprehensive framework for building, training, and evaluating a CNN for footwear image classification.

⛅ Versatile Data Pipeline (VDP) console website

Image classification convolutional neural network, using TensorFlow with an NVIDIA GPU

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

Klasifikasi Rambu Lalu Lintas

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

A treasure chest for visual classification and recognition powered by PaddlePaddle

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

Vision Transformers Implementation Visually Explained Line By Line