Popular GitHub Repositories for Mirnet Tfjs

JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js

Human: AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition, Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition

Enhance Images with Javascript and AI. Increase resolution, retouch, denoise, and more. Open Source, Browser & Node Compatible, MIT License.

Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.

? Use machine learning in JavaScript to detect eye movements and build gaze-controlled experiences.

微信小程序运行 TensorFlow 的 Demo

In-Browser Object Detection using Tiny YOLO on Tensorflow.js

TensorFlow JS models for MIRNet for low-light? image enhancement

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.

Pytorch to Keras/Tensorflow/TFLite conversion made intuitive

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.

?Change the world, it will become a better place. | 以科研和竞赛为导向的最好的YOLO实践框架!

Tiny YOLO v2 object detection with tensorflow.js.

A framework using TensorFlow.js for Deep Reinforcement Learning

Messenger chatbot builder for Node.js. https://intelligo.js.org

PiGallery: AI-powered Self-hosted Secure Multi-user Image Gallery and Detailed Image analysis using Machine Learning, EXIF Parsing and Geo Tagging

Official repository of the book "Deep learning in the browser" published by Bleeding Edge Press August 2018. Find here all of the source code of the demos!

Training a Rock Paper Scissors model in the browser via TFJS - Learn along style

Object Detection using Yolov7 in tensorflow.js