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Image Transfer and Upscaling API

This service provides APIs to perform image upscaling and style transfer (Monet style) using Machine Learning models. The project is built using Flask, a lightweight WSGI web application framework.

git clone <repository-url>
cd <project-directory>
Install the dependencies using pip.
pip install -r requirements.txt

Running the Application

Run the application with the following command:

 python3 -m flask run --host=0.0.0.0

The application should start and be accessible at localhost:5000.

API Endpoints

The application exposes two API endpoints:

/monet: POST endpoint which accepts an image file and returns the image stylized in the style of Monet paintings.

/upscale: POST endpoint which accepts an image file and returns the upscaled version of the image. #File Structure app.py: This is the main application file which runs the Flask application and defines the API endpoints. models/models.py: This file contains the model loading and prediction functions.

models/models.py

tensor_to_image(tensor): Converts a TensorFlow tensor to an image and saves it to 'upscaled_image.jpg'.

request_to_image(request): Converts a Flask request object containing an image to a numpy array.

_monet(image, upscale=False): Accepts an image as input and returns the image stylized in the style of Monet paintings.

_upscale(image): Accepts an image as input and returns the upscaled version of the image.

Sending Requests to the API

For both endpoints, the image file should be included in the request as form data with the key 'image'. Here is an example using curl:

Copy code
curl -X POST -F "image=@<image-file-path>" http://localhost:5000/monet
Copy code
curl -X POST -F "image=@<image-file-path>" http://localhost:5000/upscale
Replace <image-file-path> with the path to your image file.

Notes

The model files for the Monet style transfer (models/monet_generator) are not included in this repository. You need to download them separately and place them in the correct location. Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

docker buildx build --platform linux/amd64,linux/arm64 -t joshuapeddle/imagetransfer-server:0.0.2 --push .

docker run -p 5000:5000 joshuapeddle/imagetransfer-server:0.0.2

Imagekit upload styles

pip install Imagekit
python imagekit_upload.py

About

Flask server that provides access to an arbitrary image style transfer model. Client: https://github.com/JoshuaPeddle/ImageTransfer-client

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