MocapNET V4

Welcome to the MocapNET V4 documentation! 🎉

🔗 Original Documentation: Find the original docs at README_ORIGINAL.md.

This snapshot from the tag mnet4 branch is brought to you directly from the official MocapNET repo. Dive into the world of motion capture with ease!

🚀 Getting Started: Developer Installation

To get up and running with MocapNET V4, follow these simple steps. This script will build and run a Docker image:

cd MocapNET/tree/mnet4/docker
bash build_and_deploy.sh

🎬 How to Use

Quick Start with a Sample Video

Get started by downloading a sample video:

wget http://ammar.gr/mocapnet/shuffle.webm -O shuffle.webm

Run the Magic ✨

Execute this command:

python3 -m mediapipeHolisticWebcamMocapNET --from shuffle.webm --ik 0.001 99 99 --smooth 60 10 --all --save --plot --headless 2

Command-Line Options Explained

--headless: Skip the live video display. Ideal for headless servers or GUI-less environments.
--live: Launches a live demo. Functionalities may vary.
--mt: Enable multi-threading for better performance on multi-core CPUs.
--calib [filename]: Use a specific calibration file for camera adjustments.
--frameskip [number]: Skip a set number of frames to reduce load or speed up processing.
--nnsubsample [number]: Run the neural network at set intervals (e.g., every 2nd frame).
--ik [float int int]: Set parameters for inverse kinematics optimization.
--smooth [float float]: Apply smoothing to motion capture data.
--noik: Turn off inverse kinematics processing.
--aspectCorrection [float]: Adjust video or image aspect ratio.
--noise [float]: Add noise to input for testing under varied conditions.
--size [int int]: Define video/image dimensions.
--scale [float]: Scale the output motion data.
--plot: Plot BVH channels for skeletal animation visualization.
--all: Activate all processing features (body, eyes, mouth, hands).
--nobody: Disable body joint estimation.
--face: Enable face joint estimation.
--eyes / --reye: Estimate right eye joints.
--mouth: Enable mouth joint estimation.
--hands: Estimate hand joints.
--save: Save outputs (images, videos, data, logs).
--engine [engine_name]: Choose a specific neural network backend.
--from [filepath]: Specify input source (video file or live feed).
--profile: Activate performance profiling.

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