python - 带有 bool 输出的opencv python颜色检测

Question

我使用这个脚本进行颜色检测:

# 导入必要的包

    import numpy as np
    import argparse
    import cv2

# 构造参数解析并解析参数

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", help = "path to the image")
args = vars(ap.parse_args())

# 加载图片

image = cv2.imread(args["image"])

# 定义边界列表

boundaries = [
        ([100,50,220],[135,80,245]),
]

# 循环边界

for (lower, upper) in boundaries:
        # create NumPy arrays from the boundaries
        lower = np.array(lower, dtype = "uint8")
        upper = np.array(upper, dtype = "uint8")

        # find the colors within the specified boundaries and apply
        # the mask
        mask = cv2.inRange(image, lower, upper)
        output = cv2.bitwise_and(image, image, mask = mask)
        print (output)

        # show the images
        cv2.imshow("images", np.hstack([image, output]))
        cv2.waitKey(0)

我需要一个用于颜色检测的 bool 变量。
我怎样才能做到这一点？

问候
托马斯

Answer 1

这是我自己的解决方案:

# 导入必要的包

import shutil
import numpy as np
import argparse
import cv2

# 构造参数解析并解析参数

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", help = "path to the image")
args = vars(ap.parse_args())

# 加载图片

image = cv2.imread(args["image"])

# 定义边界列表

boundaries = [
        ([100,50,220],[135,80,245]),
]

# 循环边界

for (lower, upper) in boundaries:

# 从边界创建 NumPy 数组

    lower = np.array(lower, dtype = "uint8")
    upper = np.array(upper, dtype = "uint8")

# 查找指定边界内的颜色并应用 mask

        mask = cv2.inRange(image, lower, upper)
        if np.sum(mask) < 100:
         shutil.move(args["image"], "/temp/")

问候
托马斯