Improve_Video-Image_quality

CodeFormer Setup and Usage Guide Prerequisites Ensure you have the following software installed on your system:

Anaconda or Miniconda Git NVIDIA CUDA Toolkit (if using a GPU) Step-by-Step Installation

1. Create and Activate the Conda Environment Open your terminal (or Anaconda Prompt) and create a new conda environment named Codeformer3 with Python 3.10:

bash Copy code conda create --name Codeformer3 python=3.10 Activate the environment:

bash Copy code conda activate Codeformer3 2. Clone the CodeFormer Repository Clone the CodeFormer repository from GitHub:

bash Copy code git clone https://github.com/sczhou/CodeFormer.git cd CodeFormer 3. Check CUDA Installation Verify your CUDA installation:

bash Copy code nvcc --version 4. Install PyTorch with CUDA Support Install PyTorch with CUDA support (ensure the version matches your CUDA toolkit):

bash Copy code conda install pytorch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 pytorch-cuda=11.8 -c pytorch -c nvidia 5. Install Required Python Packages Install the required Python packages listed in requirements.txt:

bash Copy code pip install addict future lmdb numpy opencv-python Pillow==9.5.0 requests scikit-image scipy tb-nightly tqdm yapf lpips gdown 6. Install Additional Dependencies Install additional dependencies:

bash Copy code conda install -c conda-forge dlib 7. Set Up the CodeFormer Project Run the setup script for basicsr:

bash Copy code python basicsr/setup.py develop 8. Download Pre-trained Models Download the necessary pre-trained models:

bash Copy code python scripts/download_pretrained_models.py facelib python scripts/download_pretrained_models.py dlib python scripts/download_pretrained_models.py CodeFormer 9. Install FFmpeg Ensure ffmpeg is installed and accessible:

bash Copy code conda install -c conda-forge ffmpeg 10. Run CodeFormer Inference Run the inference on an input image:

bash Copy code python inference_codeformer.py --input_path inputs/whole_imgs --output_path results -w 0.7 --bg_upsampler realesrgan --face_upsample Troubleshooting

1. ffmpeg Module Not Found If you encounter an issue with the ffmpeg module not being found:

Verify the installation of ffmpeg-python:

bash Copy code pip show ffmpeg-python Install imageio-ffmpeg:

bash Copy code pip install imageio-ffmpeg Check if ffmpeg is in your system's PATH:

bash Copy code where ffmpeg Update ffmpeg-python:

bash Copy code pip install --upgrade ffmpeg-python Modify video_util.py to use imageio as a fallback:

python Copy code try: import ffmpeg except ModuleNotFoundError: import imageio_ffmpeg as ffmpeg 2. Running Inference on Videos Ensure you have ffmpeg-python installed and try running the inference on a video file:

bash Copy code python inference_codeformer.py --bg_upsampler realesrgan --face_upsample -w 1.0 --input_path video/Startrek.avi Conclusion You have successfully set up the CodeFormer project and run inference on both images and videos. For any additional issues or specific error messages, consult the project's GitHub issues page or the community forums.