mirror of https://github.com/ZHKKKe/MODNet.git
53 lines
2.2 KiB
Markdown
53 lines
2.2 KiB
Markdown
## MODNet - WebCam-Based Portrait Video Matting Demo
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This is a MODNet portrait video matting demo based on WebCam. It will call your local WebCam and display the matting results in real time. The demo can run under CPU or GPU.
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### 1. Requirements
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The basic requirements for this demo are:
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- Ubuntu System
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- WebCam
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- Python 3+
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**NOTE**: If your device does not satisfy the above conditions, please try our [online Colab demo](https://colab.research.google.com/drive/1Pt3KDSc2q7WxFvekCnCLD8P0gBEbxm6J?usp=sharing).
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### 2. Introduction
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We use ~400 unlabeled video clips (divided into ~50,000 frames) downloaded from the internet to perform SOC to adapt MODNet to the video domain. **Nonetheless, due to insufficient labeled training data (~3k labeled foregrounds), our model may still make errors in portrait semantics estimation under challenging scenes.** Besides, this demo does not currently support the OFD trick, which will be provided soon.
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For a better experience, please:
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* make sure the portrait and background are distinguishable, <i>i.e.</i>, are not similar
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* run in soft and bright ambient lighting
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* do not be too close or too far from the WebCam
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* do not move too fast
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### 3. Run Demo
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We recommend creating a new conda virtual environment to run this demo, as follow:
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1. Clone the MODNet repository:
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```
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git clone https://github.com/ZHKKKe/MODNet.git
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cd MODNet
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```
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2. Download the pre-trained model from this [link](https://drive.google.com/file/d/1Nf1ZxeJZJL8Qx9KadcYYyEmmlKhTADxX/view?usp=sharing) and put it into the folder `MODNet/pretrained/`.
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3. Create a conda virtual environment named `modnet` (if it doesn't exist) and activate it. Here we use `python=3.6` as an example:
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```
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conda create -n modnet python=3.6
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source activate modnet
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```
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4. Install the required python dependencies (please make sure your CUDA version is supported by the PyTorch version installed):
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```
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pip install -r demo/video_matting/webcam/requirements.txt
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```
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5. Execute the main code:
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```
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python -m demo.video_matting.webcam.run
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```
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### 4. Acknowledgement
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We thank [@tkianai](https://github.com/tkianai) and [@mazhar004](https://github.com/mazhar004) for their contributions to making this demo available for CPU use.
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