建模程序 多个定时程序
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from PIL import Image, ImageEnhance
import cv2, numpy, sys, os
#adjust color temperature to 6000K
def adjust_color_temp(image, color_temp):
kelvin_table = {
1000: (255, 56, 0),
1100: (255, 71, 0),
1200: (255, 83, 0),
1300: (255, 93, 0),
1400: (255, 101, 0),
1500: (255, 109, 0),
1600: (255, 115, 0),
1700: (255, 121, 0),
1800: (255, 126, 0),
1900: (255, 131, 0),
2000: (255, 138, 18),
2100: (255, 142, 33),
2200: (255, 147, 44),
2300: (255, 152, 54),
2400: (255, 157, 63),
2500: (255, 161, 72),
2600: (255, 165, 79),
2700: (255, 169, 87),
2800: (255, 173, 94),
2900: (255, 177, 101),
3000: (255, 180, 107),
3100: (255, 184, 114),
3200: (255, 187, 120),
3300: (255, 190, 126),
3400: (255, 193, 132),
3500: (255, 196, 137),
3600: (255, 199, 143),
3700: (255, 201, 148),
3800: (255, 204, 153),
3900: (255, 206, 159),
4000: (255, 209, 163),
4100: (255, 211, 168),
4200: (255, 213, 173),
4300: (255, 215, 177),
4400: (255, 217, 182),
4500: (255, 219, 186),
4600: (255, 221, 190),
4700: (255, 223, 194),
4800: (255, 225, 198),
4900: (255, 227, 202),
5000: (255, 228, 206),
5100: (255, 230, 210),
5200: (255, 232, 213),
5300: (255, 233, 217),
5400: (255, 235, 220),
5500: (255, 236, 224),
5600: (255, 238, 227),
5700: (255, 239, 230),
5800: (255, 240, 233),
5900: (255, 242, 236),
6000: (255, 243, 239),
6100: (255, 244, 242),
6200: (255, 245, 245),
6300: (255, 246, 247),
6400: (255, 248, 251),
6500: (255, 249, 253),
6600: (254, 249, 255),
6700: (252, 247, 255),
6800: (249, 246, 255),
6900: (247, 245, 255),
7000: (245, 243, 255),
7100: (243, 242, 255),
7200: (240, 241, 255),
7300: (239, 240, 255),
7400: (237, 239, 255),
7500: (235, 238, 255),
7600: (233, 237, 255),
7700: (231, 236, 255),
7800: (230, 235, 255),
7900: (228, 234, 255),
8000: (227, 233, 255),
8100: (225, 232, 255),
8200: (224, 231, 255),
8300: (222, 230, 255),
8400: (221, 230, 255),
8500: (220, 229, 255),
8600: (218, 229, 255),
8700: (217, 227, 255),
8800: (216, 227, 255),
8900: (215, 226, 255),
9000: (214, 225, 255),
9100: (212, 225, 255),
9200: (211, 224, 255),
9300: (210, 223, 255),
9400: (209, 223, 255),
9500: (208, 222, 255),
9600: (207, 221, 255),
9700: (207, 221, 255),
9800: (206, 220, 255),
9900: (205, 220, 255),
10000: (207, 218, 255),
10100: (207, 218, 255),
10200: (206, 217, 255),
10300: (205, 217, 255),
10400: (204, 216, 255),
10500: (204, 216, 255),
10600: (203, 215, 255),
10700: (202, 215, 255),
10800: (202, 214, 255),
10900: (201, 214, 255),
11000: (200, 213, 255),
11100: (200, 213, 255),
11200: (199, 212, 255),
11300: (198, 212, 255),
11400: (198, 212, 255),
11500: (197, 211, 255),
11600: (197, 211, 255),
11700: (197, 210, 255),
11800: (196, 210, 255),
11900: (195, 210, 255),
12000: (195, 209, 255)}
r, g, b = kelvin_table[color_temp]
matrix = ( r / 255.0, 0.0, 0.0, 0.0,
0.0, g / 255.0, 0.0, 0.0,
0.0, 0.0, b / 255.0, 0.0 )
return image.convert('RGB', matrix)
# filename = '/home/water/Downloads/114_8.jpg'
# with Image.open(filename) as img:
# img = img.rotate(180)
# img_array = numpy.array(img)
# img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
# img_array[:, :, 2] = img_array[:, :, 2] *0.92
# img_array = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)
# img = Image.fromarray(img_array)
# img.save('/home/water/Downloads/114_8_去红.jpg')
# # img = adjust_color_temp(img, 6000)
# # img.save('/home/water/Downloads/114_8_去红_调色温.jpg')
# # enh = ImageEnhance.Brightness(img)
# # img = enh.enhance(0.9)
# # img.save('/home/water/Downloads/114_8_去红_调色温_亮度.jpg')
# # enh = ImageEnhance.Contrast(img)
# # img = enh.enhance(1.1)
# # img.save('/home/water/Downloads/114_8_去红_调色温_亮度_对比度.jpg')
# # enh = ImageEnhance.Color(img)
# # img = enh.enhance(1.1)
# # img.save('/home/water/Downloads/114_8_去红_调色温_亮度_对比度_色彩平衡.jpg')
def decrease_red(img, threshold=0.94):
img_array = numpy.array(img)
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
img_array[:, :, 2] = img_array[:, :, 2] * threshold
img_array = cv2.cvtColor(img_array, cv2.COLOR_BGR2RGB)
img = Image.fromarray(img_array)
return img
def adjust_hsv(img, h=6):
img_array = numpy.array(img)
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2HSV)
img_array[:, :, 0] = img_array[:, :, 0] + h
img_array = cv2.cvtColor(img_array, cv2.COLOR_HSV2RGB)
img = Image.fromarray(img_array)
return img
# 用lab模式调整图像, a通道的中心点的值从1.0偏移到0.89,可以更完美的解决偏红问题,这块应该是更优的图片偏色调整方案,属于“真·无损调整”。
def adjust_lab(img, a=0.89):
img_array = numpy.array(img)
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2LAB)
img_array[:, :, 1] = img_array[:, :, 1] * a
img_array = cv2.cvtColor(img_array, cv2.COLOR_LAB2RGB)
img = Image.fromarray(img_array)
return img
if __name__ == '__main__':
if len(sys.argv) == 1:
path = '.'
elif len(sys.argv) == 2:
path = sys.argv[1]
path = os.path.abspath(path)
for filename in os.listdir(path):
if filename.endswith('调色优化.jpg'): continue
img = Image.open(os.path.join(path, filename))
img = img.rotate(180)
# img = decrease_red(img)
img = adjust_hsv(img)
# img = adjust_lab(img)
img.save(os.path.join(path, filename.replace('.jpg', '_调色优化.jpg')))