import cv2
import requests
from io import BytesIO
from PIL import Image

from segment_anything import SamPredictor, sam_model_registry
from segment_anything import SamAutomaticMaskGenerator, sam_model_registry
import matplotlib.pyplot as plt
import numpy as np

def segment_image_from_url(image_url):
    sam = sam_model_registry["vit_h"](checkpoint="sam_vit_h_4b8939.pth")
    mask_generator = SamAutomaticMaskGenerator(sam)

    response = requests.get(image_url)
    img = Image.open(BytesIO(response.content))
    image = np.array(img)
    
    masks = mask_generator.generate(image)

    plt.figure(figsize=(20,20))
    plt.imshow(image)
    show_anns(masks)
    plt.axis('off')
    output_file = 'segmented_image.png'
    plt.savefig(output_file)
    plt.close()
    return output_file

def show_anns(anns):
    if len(anns) == 0:
        return
    sorted_anns = sorted(anns, key=(lambda x: x['area']), reverse=True)
    ax = plt.gca()
    ax.set_autoscale_on(False)
    polygons = []
    color = []
    for ann in sorted_anns:
        m = ann['segmentation']
        img = np.ones((m.shape[0], m.shape[1], 3))
        color_mask = np.random.random((1, 3)).tolist()[0]
        for i in range(3):
            img[:,:,i] = color_mask[i]
        ax.imshow(np.dstack((img, m*0.35)))

# Example usage
# image_url = 'https://example.com/path/to/image.jpg'
# output_file = segment_image_from_url(image_url)
# print(f"Segmented image saved to {output_file}")