RIDNet_100k_denoiser

RIDNet IMAGE DENOISOR

Model: https://github.com/lienghongky/RIDNet_Denoisor UI Tools: https://github.com/lienghongky/PicyShake

FILEPATH

"""

Project Structure:

• main.py: The main entry point of the project.
• utils.py: Contains utility functions used in the project.
• datasets/: Directory containing the dataset for training and testing.
• models/: Directory containing the trained models.
• model_checkpoints: Save model every epoch

How to Run Train Test:

1. Install the required dependencies by running pip install -r requirements.txt.
2. Install the required dependencies by running pip install -r requirements.txt.
3. Prepare the dataset by placing the training and testing data in the datasets/ directory. or run python preprocess.py, By runing this script the following directories will be created.

    # datasets directory structure
    # datasets
    # ├── train
    # │   ├── groundtruth
    # │   │   ├── 0001.png
    # │   │   ├── 0002.png
    # │   │   ├── ...
    # │   │   └── 1000.png
    # │   └── input
    # │       ├── 0001.png
    # │       ├── 0002.png
    # │       ├── ...
    # │       └── 1000.png
    # ├── test
    # │   ├── groundtruth
    # │   │   ├── 0001.png
    # │   │   ├── 0002.png
    # │   │   ├── ...
    # │   │   └── 100.png
    # │   └── input
    # │       ├── 0001.png
    # │       ├── 0002.png
    # │       ├── ...
    # │       └── 100.png
    # └── validation
    #     ├── groundtruth
    #     │   ├── 0001.png
    #     │   ├── 0002.png
    #     │   ├── ...
    #     │   └── 100.png
    #     └── input
    #         ├── 0001.png
    #         ├── 0002.png
    #         ├── ...
    #         └── 100.png
    ```
 
4. Run the train script by executing `python train.py`.
5. Run the test script by executing `python test.py`.