Initial clean project import

2026-06-19 18:41:41 +08:00
commit a13b804c7a
1306 changed files with 220568 additions and 0 deletions
@@ -0,0 +1,50 @@
+## MODNet - Custom Portrait Video Matting Demo
+This is a MODNet portrait video matting demo that allows you to process custom videos.
+
+### 1. Requirements
+The basic requirements for this demo are:
+- Ubuntu System
+- Python 3+
+
+
+### 2. Introduction
+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.
+
+
+For a better experience, please make sure your videos satisfy:
+
+*   the portrait and background are distinguishable, <i>i.e.</i>, are not similar
+*   captured in soft and bright ambient lighting
+*   the contents do not move too fast
+
+### 3. Run Demo
+We recommend creating a new conda virtual environment to run this demo, as follow:
+
+1. Clone the MODNet repository:
+    ```
+    git clone https://github.com/ZHKKKe/MODNet.git
+    cd MODNet
+    ```
+
+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/`.
+
+
+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:
+     ```
+    conda create -n modnet python=3.6
+    source activate modnet
+    ```
+
+4. Install the required python dependencies (please make sure your CUDA version is supported by the PyTorch version installed):
+    ```
+    pip install -r demo/video_matting/custom/requirements.txt
+    ```
+
+5. Execute the main code:
+    ```
+    python -m demo.video_matting.custom.run --video YOUR_VIDEO_PATH
+    ```
+    where `YOUR_VIDEO_PATH` is the specific path of your video.  
+    There are some optional arguments:
+     - `--result-type (default=fg)` : fg - save the alpha matte; fg - save the foreground
+     - `--fps (default=30)` : fps of the result video