MPyReq MATLAB Interface Builder

MPyReq MATLAB Interface Builder

Build a MATLAB interface to a Python/PyTorch model repository using the MPyReq framework.

When to Use

• User asks to interface MATLAB with a Python image processing or computer vision model (segmentation, depth estimation, object detection, image generation, super-resolution, pose estimation, optical flow, salient object detection, etc.)
• User provides a GitHub repository URL for a vision/image model and wants to call it from MATLAB
• User asks to "create an MPyReq wrapper" or "MPyReq demo" for an image/CV model
• User wants to run a pip-installable vision model library (e.g., Cellpose, SAM2, Depth-Pro, BiRefNet, StarDist) from MATLAB

When Not to Use

• General-purpose Python-MATLAB interfacing (no vision/image model involved)
• Non-vision models: NLP, audio, tabular, reinforcement learning, time-series
• Model deployment, containerization, or inference servers
• Pure MATLAB image processing workflows with no Python dependency
• Creating Python code (this skill creates MATLAB code that calls Python)

Prerequisites: MPyReq on the MATLAB Path

Before generating any demo script, verify that MPyReq is available. Run which MPyReq via the MATLAB MCP server (if available) or ask the user to confirm.

If MPyReq is NOT on the MATLAB path:

1. Download MPyReq from the MATLAB File Exchange: https://mathworks.com/matlabcentral/fileexchange/182230-matlab-based-python-requirements-manager
2. Install it — either:
   • Open the downloaded .mltbx file in MATLAB (double-click), which installs it as a MATLAB Add-On automatically, or
   • Extract the files and add the folder containing MPyReq.m to the MATLAB path:

     addpath("/path/to/mpyreq");
     savepath; % persist across sessions
     

3. Verify by running which MPyReq in MATLAB — it should return the path to MPyReq.m.

Do not proceed with demo generation until MPyReq is confirmed on the path.

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