Mask-RCNN-TF2
human-action-classification
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| Mask-RCNN-TF2 | human-action-classification | |
|---|---|---|
| 1 | 1 | |
| 299 | 199 | |
| - | - | |
| 1.3 | 1.8 | |
| about 1 year ago | over 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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Mask-RCNN-TF2
human-action-classification
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Exercise recognition using HRNet
Train another classification model for each exercise which will be feed with image with drawn keypoints. Something like this - https://github.com/dronefreak/human-action-classification
What are some alternatives?
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
InvoiceNet - Deep neural network to extract intelligent information from invoice documents.
ActionAI - Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
ssd_keras - A Keras port of Single Shot MultiBox Detector
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:
medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
These-People-Do-Not-Exist - AI that generates human faces which have never been seen before. The future is now 😁
Keypoint_Communities - [ICCV '21] In this repository you find the code to our paper "Keypoint Communities".
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.