img = np.zeros((600, 800, 3), np.uint8) # 创建空图像 cv2.namedWindow('image') # 创建空窗口 cv2.setMouseCallback('image', onmouse) # 将回调函数与窗口绑定 while(1): cv2.imshow('image', img) k = cv2.waitKey(1) & 0xFF if k =
可以通过运行以下代码块来进行简单的图像加载和显示测试: importcv2deftest_opencv():image=cv2.imread('test_image.jpg')ifimageisnotNone:cv2.imshow('Test Image',image)cv2.waitKey(0)cv2.destroyAllWindows()return"测试成功:图像加载正常"else:return"测试失败:图像加载不成功"print(test_opencv()) 1. 2....
我们将使用cv2.inRange()函数来实现这一点。 # 创建掩码mask=cv2.inRange(hsv_image,lower_white,upper_white) 1. 2. 步骤6:显示结果 最后,我们将显示原始图像和掩码图像,以便我们可以清楚地看到非白色区域。 # 显示原始图像和掩码图像cv2.imshow('Original Image',image)cv2.imshow('Mask',mask)cv2.waitKey...
Load the image using OpenCV and convert it to grayscale img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE) Apply adaptive thresholding to obtain binary image _, img = cv2.threshold(img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU) Remove noise from the image using GaussianBlur filter img = cv2...
cv2.imshow('image',img)cv2.waitKey(0)cv2.destroyAllWindows() 在我的环境下(windows10 x64)运行结果如下: 下面解释上面用到的一些函数 cv2.waitKey()是一个键盘绑定函数。它的参数是一个毫秒数。这个函数等待特定的毫秒,如果在这个时间之内有按键按下,它就会返回相应按键的 ASCII 码(int 类型),然后程序继...
#原使用用到关于CvBridge的 from cv_bridge import CvBridge # 创建CvBridge对象 bridge = CvBridge() # 将OpenCV图像转换为ROS图像消息 image_msg = bridge.cv2_to_imgmsg(frame, encoding="bgr8") # 将ROS图像消息转换为OpenCV图像 image_msg = bridge.imgmsg_to_cv2(frame, encoding="bgr8") 解决方案如...
cv2.imshow('image',img) k = cv2.waitKey(0) # wait for ESC key toexitifk == 27: cv2.destroyAllWindows() # wait for 's' key to save andexitelif k == ord('s'): cv2.imwrite('black.png',img) cv2.destroyAllWindows() 运行结果如下: ...
cvt_image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) im_pil = Image.fromarray(cvt_image) # resize the array (image) then PIL image im_resized = im_pil.resize((224, 224)) img_array = image.img_to_array(im_resized) image_array_expanded = np.expand_dims(img_array, axis = 0) ...
cv.imshow('image',img) k=cv.waitKey(0)ifk == ord('s'):#wait for 's' key to save and exitcv.imwrite('1.png',img) cv.destroyAllWindows()else: cv.destroyAllWindows() 四、图像的基本操作 创建图片 1.创建三通道 importnumpy as npimportcv2 as cv#三通道creat_img3 = np.zeros([400...
image = cv2.imread(imgPath)使用 OpenCV 提供的方法读取图片。img2gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)转化为灰度图。如下图：原图是这样的：cv2.Laplacian(img2gray, cv2.CV_64F)对图片用 3x3 拉普拉斯算子做卷积，这里的cv2.CV_64F就是拉普拉斯算子。Welcome to join learning group: Six ...