cv2.imshow('gray', gray)
时间: 2023-08-20 09:32:16 浏览: 32
cv2.imshow('gray', gray) 是将转换成灰度图像的图像以灰度模式显示在名为 "gray" 的窗口中的代码。
其中,'gray' 是窗口名称,可以自定义;gray 是转换成灰度图像后的图像数据。如果原始图像是彩色图像,则需要使用 cv2.cvtColor() 函数将其转换为灰度图像。
示例代码:
```python
import cv2
# 读取彩色图像
img = cv2.imread('image.jpg')
# 将彩色图像转换为灰度图像
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 在名为 "gray" 的窗口中显示灰度图像
cv2.imshow('gray', gray)
# 等待键盘输入
cv2.waitKey(0)
# 关闭窗口
cv2.destroyAllWindows()
```
相关问题
请帮我优化一下这段代码if __name__=="__main__": input_dir = "./1.jpg" original_img, gray_img, RedThresh, closed, opened = Img_Outline(input_dir) box, draw_img = findContours_img(original_img,opened) #draw_img = findContours_img(original_img, opened) result_img = Perspective_transform(box,original_img) cv2.imshow("original", original_img) cv2.imshow("gray", gray_img) cv2.imshow("closed", closed) cv2.imshow("opened", opened) cv2.imshow("draw_img", draw_img) cv2.imshow("result_img", result_img) cv2.waitKey(0) cv2.destroyAllWindows()
可以考虑将代码分成几个函数,每个函数实现一个具体的功能,提高代码的可读性和可维护性。例如:
```python
def main():
input_dir = "./1.jpg"
original_img, gray_img, RedThresh, closed, opened = Img_Outline(input_dir)
box, draw_img = findContours_img(original_img, opened)
result_img = Perspective_transform(box, original_img)
show_images(original_img, gray_img, closed, opened, draw_img, result_img)
def Img_Outline(input_dir):
# 实现图像处理功能
pass
def findContours_img(original_img, opened):
# 实现图像处理功能
pass
def Perspective_transform(box, original_img):
# 实现图像处理功能
pass
def show_images(original_img, gray_img, closed, opened, draw_img, result_img):
# 显示图像
cv2.imshow("original", original_img)
cv2.imshow("gray", gray_img)
cv2.imshow("closed", closed)
cv2.imshow("opened", opened)
cv2.imshow("draw_img", draw_img)
cv2.imshow("result_img", result_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
```
这样可以使得代码更加清晰,每个函数只负责一个功能,易于维护和扩展。
import cv2 import numpy as np def getContours(img): contours, hierarchy = cv2.findContours( img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE ) for cnt in contours: area = cv2.contourArea(cnt) print(area) if area > 500: cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3) path = "/home/robot/code.py/shape.jpg" img = cv2.imread(path) imgContour = img.copy() imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1) imgCanny = cv2.Canny(imgBlur, 50, 50) getContours(imgCanny) imgBlank = np.zeros_like(img) cv2.imshow("Original", img) cv2.imshow("Gray", imgGray) cv2.imshow("Blur", imgBlur) cv2.imshow("Canny", imgCanny) cv2.imshow("Blank", imgContour) cv2.waitKey(0)有什么bug
代码中存在两个问题:
1. 在导入 cv2 模块时,应该使用以下方式:
```python
import cv2
import numpy as np
```
2. 在调用 ``cv2.drawContours()`` 函数时,需要将第一个参数改为 ``imgContour``,因为 ``imgContour`` 是我们要绘制轮廓的图像。
修改后的代码如下:
```python
import cv2
import numpy as np
def getContours(img):
contours, hierarchy = cv2.findContours(
img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE
)
for cnt in contours:
area = cv2.contourArea(cnt)
print(area)
if area > 500:
cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
path = "/home/robot/code.py/shape.jpg"
img = cv2.imread(path)
imgContour = img.copy()
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1)
imgCanny = cv2.Canny(imgBlur, 50, 50)
getContours(imgCanny)
imgBlank = np.zeros_like(img)
cv2.imshow("Original", img)
cv2.imshow("Gray", imgGray)
cv2.imshow("Blur", imgBlur)
cv2.imshow("Canny", imgCanny)
cv2.imshow("Contour", imgContour)
cv2.waitKey(0)
```