PoseNDF
CustomPose-Classification-Mediapipe
| PoseNDF | CustomPose-Classification-Mediapipe | |
|---|---|---|
| 1 | 1 | |
| 200 | 10 | |
| - | - | |
| 0.8 | 10.0 | |
| about 1 year ago | over 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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PoseNDF
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POSE-NDF — modeling human pose manifolds with neural distance fields
Project | Paper | Code
CustomPose-Classification-Mediapipe
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Custom Human Pose Classification using Mediapipe
git clone https://github.com/naseemap47/CustomPose-Classification-Mediapipe.git cd CustomPose-Classification-Mediapipe git checkout custom
What are some alternatives?
DeepPoseKit - a toolkit for pose estimation using deep learning
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
SMPL - NumPy, TensorFlow and PyTorch implementation of human body SMPL model and infant body SMIL model.
tflite2tensorflow - 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.
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
clip-fields - Teaching robots to respond to open-vocab queries with CLIP and NeRF-like neural fields
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.