deep-high-resolution-net.pytorch
openpose
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| deep-high-resolution-net.pytorch | openpose | |
|---|---|---|
| 4 | 36 | |
| 4,190 | 29,867 | |
| - | 1.6% | |
| 0.0 | 5.1 | |
| over 1 year ago | 14 days ago | |
| Cuda | C++ | |
| MIT License | GNU General Public License v3.0 or later |
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deep-high-resolution-net.pytorch
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Deadlift videos needed [AI]
I am sure you have some great ideas in mind for your model design, but a quick tip (from having worked on a similar project) - it may be very challenging to simply take raw videos as input (especially with unconstrained camera viewpoints) without doing some feature extraction/keypoint detection first. For example, open-source plug-and-play 2D keypoint detectors are extremely good nowadays (e.g HRNet), and explicitly detecting 2D keypoints before classifying deadlift videos as "good" or "bad" will likely make the task more feasible!
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[D] HRNET- Human Pose Estimation [Implementation]
The repo is well maintained on GitHub and I have replicated the author's work. But I didn't get much understanding of how things are working there. I didn't see any results.
- Help finding an appropriate model for human pose estimation
- Real time 3d reconstruction with known parameters of cameras and environment?
openpose
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AI "Artists" Are Lazy, and the Ultimate Goal of AI Image Generation (hint: its sloth)
Open Pose, a multi-person keypoint detection library for body, face, hands, and foot estimation [10], is used for posing generated characters;
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Analyze defects and errors in the created images
OpenPose
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[D] Which open source models can replicate wonder dynamics's drag'n'drop cg characters?
Perhaps something like OpenPose for pose estimation?
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Do we have Locally Run AI mocap yet?
OpenPose looks like what you're looking for, it seems to have plugins for Unity. I can't say I've used it though.
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Let's take a break!
You are correct. Open Pose has two keypoints for the eyes and two more for the ears. By saying were the ears are you automatically influence the angle of the head. You can see more about it on this github page. Just scroll a tiny bit and you can see a gif of the nodes overlapped on humans
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Accelerate Machine Learning Local Development and Test Workflows with Nvidia Docker
FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 # https://hub.docker.com/r/nvidia/cuda ENV DEBIAN_FRONTEND=noninteractive # install the dependencies for building OpenPose RUN apt-get update && # The rest is ignored for brevity. RUN pip3 install --no-cache-dir # The rest is ignored for brevity. # install cmake, clone OpenPose and download models RUN wget https://cmake.org/files/v3.20/cmake-3.20.2-linux-x86_64.tar.gz && \ # The rest is ignored for brevity. WORKDIR /openpose/build RUN alias python=python3 && cmake -DBUILD_PYTHON=OFF -DWITH_GTK=OFF -DUSE_CUDNN=ON .. # Build OpenPose. Cudnn 8 causes memory issues this is why we are using base with CUDA 10 and Cudnn 7 # Fix for CUDA 10.0 and Cudnn 7 based on the post below. # https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/1753#issuecomment-792431838 RUN sed -ie 's/set(AMPERE "80 86")/#&/g' ../cmake/Cuda.cmake && \ sed -ie 's/set(AMPERE "80 86")/#&/g' ../3rdparty/caffe/cmake/Cuda.cmake && \ make -j`nproc` && \ make install WORKDIR /openpose
- nub needs some directions
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full body tracking with WiFi signals by utilizing deep learning architectures
One of the best cam only libraries (no depth sensor) I've seen is openpose, I ran it through a 360 camera and it was able to track body, face, and fingers really well even with spherical distortion from the 360 cam. example 360
- How to do body tracking for (real) camera
- How to get rotation (yaw/pitch/roll) from face detection keypoints?
What are some alternatives?
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
BlazePose-tensorflow - A third-party Tensorflow Implementation for paper "BlazePose: On-device Real-time Body Pose tracking".
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
UniPose - We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datase