Initial commit

Author: jagin

.gitignore

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+# Idea / PyCharm
+.idea/
+
+# files from the mac
+.DS_Store
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*.class
+
+# Project dependant
+output/

LICENSE

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+MIT License
+
+Copyright (c) 2018 Jarek Gilewski
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# Detectron2 pipeline
+
+Modular image processing pipeline using OpenCV and Python generators powered by [Detectron2](https://github.com/facebookresearch/detectron2).  
+
+For detailed description how to construct image processing pipeline using OpenCV and Python generators
+read the following Medium stories in order:
+* [Modular image processing pipeline using OpenCV and Python generators](https://medium.com/deepvisionguru/modular-image-processing-pipeline-using-opencv-and-python-generators-9edca3ccb696)
+* [Video processing pipeline with OpenCV](https://medium.com/deepvisionguru/video-processing-pipeline-with-opencv-ac10187d75b)
+* How to embed Detectron2 in your computer vision project
+
+## Setup environment
+
+This project is using [Conda](https://conda.io) for project environment management.
+
+Setup the project environment:
+
+    $ conda env create -f environment.yml
+    $ conda activate detectron2-pipeline
+    
+or update the environment if you `git pull` the repo previously:
+
+    $ conda env update -f environment.yml
+    
+Install Detectron2 in a folder one level above the `detectron2-pipeline` project folder
+
+    $ cd ..
+    $ git clone https://github.com/facebookresearch/detectron2.git
+    $ cd detectron2
+    $ git checkout 3def12bdeaacd35c6f7b3b6c0097b7bc31f31ba4
+    $ python setup.py build develop
+    
+We checkout `3def12bdeaacd35c6f7b3b6c0097b7bc31f31ba4` commit to ensure that you can use the code
+out of the box with this repo.
+
+If you got any problems with Detectron2 installation please refer to
+[INSTALL.md](https://github.com/facebookresearch/detectron2/blob/3def12bdeaacd35c6f7b3b6c0097b7bc31f31ba4/INSTALL.md).
+
+## Demo
+
+Run the command to execute inferences on images from the selected folder:
+
+    $ python process_images.py -i assets/images/friends -p
+
+By default the instance segmentation model is used from `configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml`.
+You can try other models with `--config-file` option, for example:
+
+    $ python process_images.py -i assets/images/friends -p --config-file configs/COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml
+
+For video processing run:
+
+    $ python process_video.py -i assets/videos/walk.small.mp4 -p -d -ov walk.small.mp4
+
+## Tests
+
+`pytest` is used as a test framework. All tests are stored in `tests` folder. Run the tests:
+
+```bash
+$ pytest
+```
+
+## Resources and Credits
+
+* For Unix like pipeline idea credits goes to this [Gist](https://gist.github.com/alexmacedo/1552724)
+* The source of the example images and videos is [pixbay](https://pixabay.com)
+* Some ideas and code snippets are borrowed from [pyimagesearch](https://www.pyimagesearch.com/)
+* Color constants from [Python Color Constants Module](https://www.webucator.com/blog/2015/03/python-color-constants-module/)
+* [Detectron2](https://github.com/facebookresearch/detectron2)
+* [Applications of Foreground-Background separation with Semantic Segmentation](https://www.learnopencv.com/applications-of-foreground-background-separation-with-semantic-segmentation/)
+
+## License
+
+[MIT License](LICENSE)