import numpy as np
import copy
import cv2

#顏色空間轉(zhuǎn)換
def Get_YUV420(img_path):
    img = cv2.imread(img_path)
    
    yuv2 = cv2.cvtColor(img, cv2.COLOR_BGR2YUV_IYUV)
    # cv2.COLOR_BGR2YUV_YV12
    # cv2.COLOR_BGR2YUV_IYUV
    # cv2.COLOR_BGR2YUV_I420
    
    width = img.shape[1]
    UV_width = width // 2
    height = img.shape[0]
    UV_height = height // 2
    
    
    # #YUV420 UV的一個像素相當(dāng)于Y通道2X2的像素塊
    # UV_width =int(width / 4)
    # UV_heigth = height
    
    #Y通道是跟原圖像相同size
    Y = yuv2[0:height, 0:width]
    
    #U通道是Y后面
    tmp_U = yuv2[height : height + int(height / 4), 0 : width]
    tmp_V = yuv2[height + int(height / 4) : height + int(height / 2), 0 : width]
    
    U = tmp_U.reshape(UV_width, UV_height)
    V = tmp_V.reshape(UV_width, UV_height)
    
    return Y, U, V

import DCT_utils

jpeg_img_path = "D:/neural_network/Webp/dataset_128/dataset/jpeg1/jpeg1_70/1.jpeg"

#顏色空間變換
#使用DCT_utils.進(jìn)行函數(shù)實例化，Get_YUV420是DCT_utils.py中寫的一個函數(shù)
jpeg_Y, jpeg_U, jpeg_V = DCT_utils.Get_YUV420(jpeg_img_path)

import sys
sys.path.append("D:/neural_network/Webp/Encoder_analyze")#這里寫上路徑就行