Create state-of-the-art object detection and instance segmentation models.
Using either the TFJS Task API or the TFLITE Web API you can now deploy Tensorflow Lite models on the web without even needing to convert them into Tensorflow.js format.
The TensorFlow Lite Model Maker library is a high-level library that simplifies the process of training a TensorFlow Lite model using a custom dataset. It uses transfer learning to reduce the amount of training data required and shorten the training time.
D2Go is a production-ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms.
With the recently released official Tensorflow 2 support for the Tensorflow Object Detection API, it's now possible to train your own custom object detection models with Tensorflow 2.
Learn how to use the Tensorflow Object Detection API with Tensorflow 2
Train a custom yolo object detection model in PyTorch
Use and create YOLOV3 models with keras-yolo3.
Use YOLOv3 with OpenCV to detect objects in both images and videos.
Learn how to use YOLO for Object Detection.
Getting started with Mask R-CNN in Keras
