客户网站分析搜索网排名

目录

python 统计相同像素值个数

最大值附近的值

python 统计相同像素值个数

import cv2
import numpy as np
import time
from collections import Counter# 读取图像
image = cv2.imread('mask16.jpg')# 将图像转换为灰度图像
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)area=gray_image.shape[0]*gray_image.shape[1]
print('shape',gray_image.shape)
# 将灰度图像展平为一维数组
pixels = gray_image.flatten()start=time.time()
# 使用 Counter 统计每个像素值的出现次数
pixel_counts = Counter(pixels)most_commons = pixel_counts.most_common(10)print('time',time.time()-start)
count=0
for most_common in most_commons:count+=most_common[1]print(most_common,count,count/len(pixels))
print(count,count/len(pixels))
# 打印每个像素值及其出现次数
# for pixel_value, count in pixel_counts.items():
#     print(f"Pixel value {pixel_value}: {count} times")

最大值附近的值

import cv2
import numpy as np
import time
from collections import Counter# 读取图像
image = cv2.imread('mask16.jpg')# 将图像转换为灰度图像
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)area=gray_image.shape[0]*gray_image.shape[1]
print('shape',gray_image.shape)
# 将灰度图像展平为一维数组
pixels = gray_image.flatten()start=time.time()
# 使用 Counter 统计每个像素值的出现次数
pixel_counts = Counter(pixels)most_commons = pixel_counts.most_common(10)print('time',time.time()-start)
count=0
max_pixel=int(most_commons[0][0])
for ii, most_common in enumerate(most_commons):if abs(max_pixel- int(most_common[0]))<5:count+=most_common[1]print(most_common,count,count/len(pixels))else:print('ffffff',most_common[0])
print(count,count/len(pixels))