import numpy as np
import cv2
from PIL import Image


# def read_img(image_path):
#     img = cv2.imread(image_path)
#     img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
#     assert len(img.shape)==3
#     return img

def read_img(image_file_buffer):
    img = Image.open(image_file_buffer).convert('RGB')
    img = np.array(img)
    assert len(img.shape)==3
    return img

# Calculates the average brightness in the specified irregular image
def calculate_average_brightness(img):
    # Average value of three color channels
    R = img[..., 0].mean()
    G = img[..., 1].mean()
    B = img[..., 2].mean()

    brightness = 0.299 * R + 0.587 * G + 0.114 * B
    return brightness, B, G, R

# Adjusting the average brightness of the target image to the average brightness of the source image
def adjust_brightness_from_src_to_dst(dst, src,path=None,if_show=None, if_info=None):
    brightness1, B1, G1, R1 = calculate_average_brightness(src)
    brightness2, B2, G2, R2 = calculate_average_brightness(dst)
    brightness_difference = brightness1 / brightness2

    if if_info:
        print('Average brightness of original image', brightness1)
        print('Average brightness of target', brightness2)
        print('Brightness Difference between Original Image and Target', brightness_difference)

    # According to the average display brightness
    dstf = dst * brightness_difference

    # According to the average value of the three-color channel
    # dstf = dst.copy().astype(np.float32)
    # dstf[..., 0] = dst[..., 0] * (B1 / B2)
    # dstf[..., 1] = dst[..., 1] * (G1 / G2)
    # dstf[..., 2] = dst[..., 2] * (R1 / R2)

    # To limit the results and prevent crossing the border,
    # it must be converted to uint8, otherwise the default result is float32, and errors will occur.
    dstf = np.clip(dstf, 0, 255)
    dstf = np.uint8(dstf)

    ma,na,_ = src.shape
    mb,nb,_ = dst.shape
    result_show_img = np.zeros((max(ma, mb), 3 * max(na, nb), 3))
    result_show_img[:mb, :nb, :] = dst
    result_show_img[:ma, nb:nb + na, :] = src
    result_show_img[:mb, nb + na:nb + na + nb, :] = dstf
    result_show_img = result_show_img.astype(np.uint8)

    if if_show:
        cv2.imshow('-', cv2.cvtColor(result_show_img, cv2.COLOR_BGR2RGB))
        cv2.waitKey(0)
        cv2.destroyAllWindows()

    if path != None:
        cv2.imwrite(path, cv2.cvtColor(result_show_img, cv2.COLOR_BGR2RGB))

    return dstf