PeekingDuck
ailia-models
| PeekingDuck | ailia-models | |
|---|---|---|
| 5 | 4 | |
| 158 | 1,840 | |
| 0.6% | 3.2% | |
| 0.0 | 9.8 | |
| 10 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | - |
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PeekingDuck
ailia-models
-
10$ Full Body Tracking! I'm proud to release ToucanTrack (in Beta!). Get decent FBT with the power of 2 PS3 Eye Cameras and AI!
If you're looking for the differences in terms of how inference is done, I recommend you take a look at MediaPipe's source code. MediaPipe doesn't use raw code, but uses a "graph" instead (eg. pose_landmark_cpu.pbtxt), which can be visualised using MediaPipe Viz. I also used axinc-ai/ailia-models as the base (preprocessing, inference, postprocessing, etc...) which I further built upon (keypoint refinement, roi from keypoints, filtering / smoothing, etc...)
- [P] A collection of pre-trained, state-of-the-art AI models
- Ailia-models: A collection of pre-trained, state-of-the-art AI models
What are some alternatives?
tensorflow_Realtime_Multi-Person_Pose_Estimation - Multi-Person Pose Estimation project for Tensorflow 2.0 with a small and fast model based on MobilenetV3
DeepCamera - Open-Source AI Camera. Empower any camera/CCTV with state-of-the-art AI, including facial recognition, person recognition(RE-ID) car detection, fall detection and more
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
gluon-cv - Gluon CV Toolkit
Put-In-Context - Putting Visual Object Recognition in Context
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
robotics-level-4 - This repo contains projects created using TensorFlow-Lite on Raspberry Pi and Teachable Machine. AI and ML capabilities have been integrated with Robot's software.
AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
mlapi - An easy to use/extend object recognition API you can locally install. Python+Flask. Also works with ZMES!
Nodz - Nodz : Visualize your data - Free nodes based graph generator.
Video-Dataset-Loading-Pytorch - Generic PyTorch dataset implementation to load and augment VIDEOS for deep learning training loops.