Matlab Faster Rcnn reimplemented in Python
Faster R-CNN is an object detection framework based on deep convolutional networks, which includes a Region Proposal Network (RPN) and an Object Detection Network. Both networks are trained for sharing convolutional layers for fast testing.
This repo contains a Python implementation of Faster-RCNN originally developed in Matlab.
This code works with models trained using Matlab version of Faster-RCNN which is main difference between this and py-faster-rcnn.
This code was developed for internal use in one of my projects at the end of 2015. I decided to publish it as is.
Faster R-CNN was initially described in an arXiv tech report.
Faster R-CNN Matlab version is available at faster-rcnn.
Python version is available at py-faster-rcnn.
Use provided Dockerfile to build container with all required dependencies.
Build docker container:
docker build -t faster_rcnn .
Download MATLAB Faster-RCNN models:
docker run --mount type=bind,source="$(pwd)",target=/app -w /app/models -it faster_rcnn /app/models/download_models.sh
Run detection
docker run --mount type=bind,source="$(pwd)",target=/app -w /app -it faster_rcnn python experiments/faster_rcnn.py models/000456.jpg faster_rcnn_VOC0712_ZF
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If the automatic “fetch_data” fails, you may manually download resouces from:
Faster R-CNN is released under the MIT License (refer to the LICENSE file for details).