# Quick Start ## Installation #### 1. Install PaddlePaddle Versions * PaddlePaddle >= 2.0.2 * Python >= 3.7+ Due to the high computational cost of model, PaddleSeg is recommended for GPU version PaddlePaddle. CUDA 10.0 or later is recommended. See [PaddlePaddle official website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html) for the installation tutorial. #### 2. Download the PaddleSeg repository ```shell git clone https://github.com/PaddlePaddle/PaddleSeg ``` #### 3. Installation ```shell cd PaddleSeg/Matting pip install -r requirements.txt ``` ## Download pre-trained model Download the pre-trained model in [Models](../README.md/#Models) to `pretrained_models`. Take PP-MattingV2 as an example. ```shell mkdir pretrained_models && cd pretrained_models wget https://paddleseg.bj.bcebos.com/matting/models/ppmattingv2-stdc1-human_512.pdparams cd .. ``` ## Prediction ```shell export CUDA_VISIBLE_DEVICES=0 python tools/predict.py \ --config configs/ppmattingv2/ppmattingv2-stdc1-human_512.yml \ --model_path pretrained_models/ppmattingv2-stdc1-human_512.pdparams \ --image_path demo/human.jpg \ --save_dir ./output/results \ --fg_estimate True ``` Prediction results are as follows:
**Note**: `--config` needs to match `--model_path`. ## Background Replacement ```shell export CUDA_VISIBLE_DEVICES=0 python tools/bg_replace.py \ --config configs/ppmattingv2/ppmattingv2-stdc1-human_512.yml \ --model_path pretrained_models/ppmattingv2-stdc1-human_512.pdparams \ --image_path demo/human.jpg \ --background 'g' \ --save_dir ./output/results \ --fg_estimate True ``` The background replacement effect is as follows:
**Notes:** * `--image_path` must be the specific path of an image. * `--config` needs to match `--model_path`. * `--background` can be passed into the background image path, or one of ('r','g','b','w'), representing a red, green, blue, or white background, default green if not passed. ## Video Prediction Run the following commad to predict the video, and remember to pass the video path by `--video_path`. ```shell export CUDA_VISIBLE_DEVICES=0 python tools/predict_video.py \ --config configs/ppmattingv2/ppmattingv2-stdc1-human_512.yml \ --model_path pretrained_models/ppmattingv2-stdc1-human_512.pdparams \ --video_path path/to/video \ --save_dir ./output/results \ --fg_estimate True ``` Prediction results are as follows:

## Video Background Replacement Run the following commad to replace video background, and remember to pass the video path by `--video_path`. ```shell export CUDA_VISIBLE_DEVICES=0 python tools/bg_replace_video.py \ --config configs/ppmattingv2/ppmattingv2-stdc1-human_512.yml \ --model_path pretrained_models/ppmattingv2-stdc1-human_512.pdparams \ --video_path path/to/video \ --background 'g' \ --save_dir ./output/results \ --fg_estimate True ``` The background replacement effect is as follows:

**Notes:** * `--background` can be passed into the background image path, or background video path, or one of ('r','g','b','w'), representing a red, green, blue, or white background, default green if not passed.