cv2.waitKey(0) #Convert Image To GrayScale gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) cv2.imshow('Gray', gray) cv2.waitKey(0) #Binary Thresholding ret, thresh = cv2.threshold(gray, 150, 255, cv2.THRESH_BINARY_INV) cv2.imshow('Binary Image', thresh) cv2.waitKey(0) #Crop Image...
以下是一个使用OpenCV切割图像的示例代码: importcv2defcrop_image(image_path,bounding_box):# 加载图像image=cv2.imread(image_path)# 切割图像x,y,w,h=bounding_box cropped_image=image[y:y+h,x:x+w]returncropped_image# 测试代码image_path='image.jpg'bounding_box=(100,100,200,200)cropped_image=...
img_path='E:/process_img/boundingbox/' img_name='12_extra_non_hlines.jpg' pts='E:/process_img/boundingbox/temp1.txt' src=cv.imread(img_path+img_name)#src是numpy.ndarray类型 bounding_box=np.loadtxt(pts,dtype=np.int32) # cv.imshow('ori_src',src) for line in bounding_box: pt1...
box = np.int0(.BoxPoints(rect)) # draw a bounding box arounded the detected barcode and display the image cv2.drawContours(image, [box], -1, (0, 255, 0), 3) cv2.imshow("Image", image) cv2.imwrite("contoursImage2.jpg", image) cv2.waitKey(0) 1. 2. 3. 4. 5. 6. 7. 8....
找出四个顶点的x,y坐标的最大最小值。新图像的高=maxY-minY,宽=maxX-minX。 Xs = [i[0]foriinbox] Ys= [i[1]foriinbox] x1=min(Xs) x2=max(Xs) y1=min(Ys) y2=max(Ys) hight= y2 -y1 width= x2 -x1 cropImg= image[y1:y1+hight, x1:x1+width] 裁剪出的图片如下:...
1、ythonOpenCVboundingbox并标明数据类class_name =car# b_box 左上坐标ptLeftTop =np.array(40, 145)# 本框左上坐标textleftop =# b_box 右下坐标ptRightBottom np.array(365, 400)# 框的颜point_color =(0, 255, 0)# 线的厚度thickness =2# 线的类型lineType =4src =cv2.imread(data/detect/...
image = Image.open(img_path)#print(image)crop_image = cv2.imread(img_path)#print(crop_image[0])boxes = yolo.detect_image(image)#print(boxes)top = boxes[0][0] left = boxes[0][1] bottom = boxes[0][2] right = boxes[0][3] ...
pip install opencv-python==3.4.2安装,你也可以在这里找到OpenCV安装教程,这里注意一点,OpenCV 4目前处于测试阶段,这里建议去安装OpenCV 3.4.2+。 首先,导入所需的数据包——OpenCV和NumPy。现在解析四个命令行参数,命令行参数在运行时处理,允许我们从终端更改脚本的输入。如果你对其不熟悉,建议阅读相关的内容。命令...
then OpenCV successfully performed image # stitching if status == 0: # check to see if we supposed to crop out the largest rectangular # region from the stitched image if args["crop"] > 0: # create a 10 pixel border surrounding the stitched image print("[INFO] cropping...") stitched...
除了opencv专门用来进行图像处理,可以进行像素级、特征级、语义级、应用级的图像处理外,python中还有其他库用来进行简单的图像处理,比如图像的读入和保存、滤波、直方图均衡等简单的操作,下面对这些库进行详细的介绍。 目录 一、PIL库 一、安装命令 二、Image模块 ...