import gradio as gr
import cv2
import numpy as np

def process_images(files, blending_weight=0.5):
    # Process the uploaded image files here
    # You can access the uploaded files in the 'files' parameter as a list
    # For example, you can loop through the files and perform operations on them
    images = [np.array(img) for img in files]

    # Ensure all images have the same data type (CV_8U)
    for i in range(len(images)):
        # Ensure the image is a NumPy array and has the desired data type
        if images is not None:
            images = images.astype(np.uint8)
        else:
            # Handle the case where the image couldn't be loaded
            print("Failed to load the image")

    # Perform the image operation (e.g., blending)
    result_image = images[0].copy()
    for img in images[1:]:
        result_image = cv2.addWeighted(result_image, 1 - blending_weight, img, blending_weight, 0)

    # Convert the result image to PIL format for Gradio display
    result_pil_image = cv2.cvtColor(result_image, cv2.COLOR_BGR2RGB)
    return result_pil_image

iface = gr.Interface(
    fn=process_images,
    inputs=gr.inputs.File(type="file", label="multiple files", file_count='multiple'),
    outputs=gr.outputs.Image(type="pil", label="Blended Image")
)

iface.launch()