MRCNN - greeny

Introduction

Greeny is an application which uses Mask R-CNN TF2 the Tensorflow 2 version of Mask R-CNN originally meant for object detection and scene segmentation, to add a green screen to the background of people in any video. It supports multiple people and creates an exact cut-out of the people present in the video.

Here are the demo images:

Original Image 1	New Image 1
Original Image 2	New Image 2
:--:	:--:

Here are the demo gifs:

Demo 1	Demo 1 Greened

Compatibility

1. This project requires python version to be 3.8 >= (python versions) >=3.5.
2. This project requires a gpu for faster process times.
3. This project will not work with tensorflow 1.

Installation steps

Greeny doesn't require installation.

1. You can download dependencies as follows using package manager pip.

pip install -r requirements.txt

2. Download the pre-trained weights inside the root directory mrcnn-greeny. The weights can be downloaded from this link: https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5
3. Run the script run.py

python3 run.py

4. Enter video file name

Enter video filename: video.mp4

The directory tree of the project is as follows:

mrcnn:
   helpers.py
   requirements.txt
   run.py
   Google_Colab_notebook.ipynb

Run online

| MRCNN Greeny Google Colab Notebook

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

References

Mask R-CNN
Mask R-CNN TF2
Mask-RCNN Shiny

Citations

License

APACHE LICENSE, VERSION 2.0