import cv2
import matplotlib.pyplot as plt

# 讀取圖像
image = cv2.imread('input.jpg')  # 默認(rèn)讀取為BGR格式

# 方法1：使用cv2.COLOR_BGR2GRAY轉(zhuǎn)換
gray_image1 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 顯示結(jié)果
plt.figure(figsize=(10, 5))
plt.subplot(121), plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), plt.title('Original')
plt.subplot(122), plt.imshow(gray_image1, cmap='gray'), plt.title('Grayscale (OpenCV)')
plt.show()

from PIL import Image
import numpy as np
import matplotlib.pyplot as plt

# 打開(kāi)圖像
image = Image.open('input.jpg')

# 方法1：使用convert('L')
gray_image1 = image.convert('L')  # 'L'表示亮度模式

# 方法2：手動(dòng)實(shí)現(xiàn)加權(quán)平均
rgb_image = np.array(image)
gray_image2 = np.dot(rgb_image[..., :3], [0.299, 0.587, 0.114]).astype(np.uint8)

# 顯示結(jié)果
plt.figure(figsize=(15, 5))
plt.subplot(131), plt.imshow(image), plt.title('Original')
plt.subplot(132), plt.imshow(gray_image1, cmap='gray'), plt.title('Grayscale (Pillow)')
plt.subplot(133), plt.imshow(gray_image2, cmap='gray'), plt.title('Grayscale (Manual)')
plt.show()

import cv2
import numpy as np
import matplotlib.pyplot as plt

# 讀取圖像
image = cv2.imread('input.jpg')

# 方法1：平均值法
gray_avg = np.mean(image, axis=2).astype(np.uint8)

# 方法2：加權(quán)平均法（與OpenCV相同）
gray_weighted = np.dot(image[..., :3], [0.299, 0.587, 0.114]).astype(np.uint8)

# 方法3：使用floor函數(shù)（類(lèi)似整數(shù)運(yùn)算）
gray_floor = (image[..., 0] * 299 + image[..., 1] * 587 + image[..., 2] * 114 + 500) // 1000

# 顯示結(jié)果
plt.figure(figsize=(15, 5))
plt.subplot(141), plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), plt.title('Original')
plt.subplot(142), plt.imshow(gray_avg, cmap='gray'), plt.title('Average Method')
plt.subplot(143), plt.imshow(gray_weighted, cmap='gray'), plt.title('Weighted Average')
plt.subplot(144), plt.imshow(gray_floor, cmap='gray'), plt.title('Integer Arithmetic')
plt.show()

import cv2
import numpy as np

def adaptive_grayscale(image):
    # 計(jì)算每個(gè)通道的標(biāo)準(zhǔn)差
    std_dev = np.std(image, axis=(0, 1))
    # 歸一化標(biāo)準(zhǔn)差作為權(quán)重
    weights = std_dev / np.sum(std_dev)
    # 應(yīng)用權(quán)重
    gray = np.dot(image[..., :3], weights).astype(np.uint8)
    return gray

# 使用示例
image = cv2.imread('input.jpg')
gray_adaptive = adaptive_grayscale(image)

# 顯示結(jié)果
plt.figure(figsize=(10, 5))
plt.subplot(121), plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)), plt.title('Original')
plt.subplot(122), plt.imshow(gray_adaptive, cmap='gray'), plt.title('Adaptive Grayscale')
plt.show()