This Python script utilizes the Gradio client to interact with a hosted machine learning model for background removal. It then composites the result onto a specified background image.

• Python 3.6+
• Pillow (PIL Fork) for image processing
• Gradio client for interacting with the hosted model

You can install the required packages using pip:

pip install pillow gradio_client

1. Save your script as app.py.
2. Place the image you want to process as test.jpg in the same directory as your script.
3. Save your desired background image as bg.png in the same directory.
4. Run the script using the following command:

   python app.py

The script will perform the following actions:

• Connect to the hosted model via Gradio client.
• Send test.jpg for background removal.
• Upon receiving the processed image, it will be saved as image.png in a temporary directory.
• Load image.png and bg.png, then crop and resize the background image to match the dimensions of the processed image.
• Composite the processed image onto the background image.
• Save the composited image as output.png in the same directory as your script.

The script is designed to be run as a standalone application. It does not require any command line arguments, as the file paths are hardcoded for simplicity. For different images, replace test.jpg and bg.png with your images and ensure they are in the correct directory before running the script.

The final output, output.png, will be the background removed image composited onto the specified background image and saved in the same directory as the script.

Please note that the hosted model's availability and performance are subject to the provider's policies and server status. This script is a basic example and may need adjustments for production use.