CMIF
for example)Clone the repository:
git clone https://github.com/SEEDGuard/SEEDConsistencyChecker.git
Install the required dependencies:
pip install -r requirements.txt
Download the pre-trained weights from this location:
https://drive.google.com/file/d/124tuB-Txg1nfv6mp9oc8ZRg7UhzSjC_M/view?usp=sharing
Replace the pretrained_model_path variable with the pre-trained weights location in the below file:
SEEDConsistencyChecker/core/CMIF/Utils/seed_checker.py
Run the file from SEEDConsistencyChecker
directory:
cd SEEDConsistencyChecker
python main.py --method CMIF --input_dir 'path/to/input/folder/' --output_dir 'path/to/output/folder/'
Output is stored in the path/to/output/folder/
directory.
Steps 1 and 2 will be the same.
Configure the input and output path in testing.py
:
input_dir = 'path/to/input/folder/'
output_dir = 'path/to/output/folder/'
Run the testing script from SEEDConsistencyChecker
directory:
cd SEEDConsistencyChecker
python test/CMIF/testing.py
Clone the repository:
git clone https://github.com/SEEDGuard/SEEDConsistencyChecker.git
Make sure you have Docker installed and started, follow if not Install Docker.
Replace the pretrained_model_path variable with the pre-trained weights location in the below file:
SEEDConsistencyChecker/core/CMIF/Utils/seed_checker.py
pretrained_model_path = "/app/core/CMIF/utils/t5_classification_final_ep2.mdl"
Navigate to the folder consisting of Dockerfile
Build Docker Image
docker build --tag your-image-name .
Run the Docker image inside container
Update your-image-name, your_method, dataset according to your configuration. For more info on available methods refer to our Methods list provided in README
-docker run -it your-image-name --method your_method --input_dir dataset/input/ --output_dir dataset/output/
Example:
docker build -t cmif:1.1 .
docker run -it cmif:1.1
Application is up and running. Output is generated and you can see them in the test folder
You can see the logs, files, status for the container on the Docker Desktop.
SEEDConsistencyChecker thrives on community contributions. Whether you're interested in enhancing its security features, expanding the API, or improving the current functionality, your contributions are welcome. Please refer to our contribution guideline at CONTRIBUTING.md for more information on how to contribute. Also refer to our Docker template if you are coming up with new Methods for the task.