import cv2
import numpy as np

def color_transfer(source, target):
    # Convert the images from RGB to L*a*b* color space
    source_lab = cv2.cvtColor(source, cv2.COLOR_BGR2Lab)
    target_lab = cv2.cvtColor(target, cv2.COLOR_BGR2Lab)
    
    # Split the LAB image into L, A and B channels
    source_l, source_a, source_b = cv2.split(source_lab)
    target_l, target_a, target_b = cv2.split(target_lab)
    
    # Compute mean and standard deviation for each channel in both images
    l_mean_src, l_std_src, = source_l.mean(), source_l.std()
    a_mean_src, a_std_src = source_a.mean(), source_a.std()
    b_mean_src, b_std_src = source_b.mean(), source_b.std()

    l_mean_tar, l_std_tar = target_l.mean(), target_l.std()
    a_mean_tar, a_std_tar = target_a.mean(), target_a.std()
    b_mean_tar, b_std_tar = target_b.mean(), target_b.std()
    
    # Perform the color transfer
    l_result = (source_l - l_mean_src) * (l_std_tar / l_std_src) + l_mean_tar
    a_result = (source_a - a_mean_src) * (a_std_tar / a_std_src) + a_mean_tar
    b_result = (source_b - b_mean_src) * (b_std_tar / b_std_src) + b_mean_tar
    
    # Clip and reshape the channels
    l_result = np.clip(l_result, 0, 255).astype(np.uint8)
    a_result = np.clip(a_result, 0, 255).astype(np.uint8)
    b_result = np.clip(b_result, 0, 255).astype(np.uint8)
    
    # Merge the channels back
    result_lab = cv2.merge([l_result, a_result, b_result])
    
    # Convert the resulting image from L*a*b* to RGB color space
    result = cv2.cvtColor(result_lab, cv2.COLOR_Lab2BGR)
    
    return result



def create_target_image(hex_colors):
    # Convert hex colors to RGB
    rgb_colors = [tuple(int(hex_color[i:i+2], 16) for i in (0, 2, 4)) for hex_color in hex_colors]
    
    # Create an image with the RGB colors
    target_image = np.zeros((100, len(rgb_colors), 3), dtype=np.uint8)
    for i, rgb_color in enumerate(rgb_colors):
        target_image[:, i] = rgb_color
    
    return target_image


# # Load source and target images
# source_img = cv2.imread("estampa.jpg")
# target_img = cv2.imread("cor.jpg")


# hex_colors = ['ff0000', '00ff00', '0000ff']  # Example hex colors
# target_img = create_target_image(hex_colors)

# image_bytes = io.BytesIO(source_img)
# image_np = np.array(image)

# # Perform color transfer
# transferred_img = color_transfer(source_img, target_img)

# # Return the transferred image for visualization
# cv2.imwrite("result.jpg", transferred_img)

def recolor(image_np, colors):
    colors = [color.replace('#', '') for color in colors]
    
    target_img = create_target_image(colors)
    source_bgr = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
    transferred_img = color_transfer(source_bgr, target_img)
    cv2.imwrite("result.jpg", transferred_img)
    return transferred_img