下面是输出旋转角度的代码: print("Detected rotation angle:",angle) 1. 完整代码 下面是整个流程的完整代码: importpaddleocrimportcv2# 读取图片文件image=cv2.imread('path/to/image.jpg')# 加载PaddleOCR模型ocr=paddleocr.OCR()# 检测图片旋转角度angle=ocr.get_rotate_angle(image)# 输出旋转角度print("Detec...
裁剪代码如下: import json import os import numpy as np import cv2 def get_rotate_crop_image(img, points): ''' img_height, img_width = img.shape[0:2] left = int(np.min(points[:, 0])) right = int(np.max(points[:, 0])) top = int(np.min(points[:, 1])) bottom = int(np...
AI代码解释 using OpenCvSharp;using PaddleOCRSharp;varimage=newMat("path_to_image.jpg");varangle=GetRotationAngle(image);// 计算旋转角度varrotatedImage=RotateImage(image,angle);// 使用PaddleOCR进行识别varocr=newPaddleOCR();ocr.Initialize(modelPath:@"path_to_model");varresult=ocr.Recognize(rotated...
rotation_angle() box = image.getbbox() return image.crop(box) def rotation_angle(self): x1, y1 = self.xy[0] x2, y2 = self.xy[1] angle = self.angle([x1, y1, x2, y2], [0, 0, 10, 0]) * -1 return self.image.rotate(angle, expand=True) def angle(self, v1, v2):...
box = image.getbbox()returnimage.crop(box)defrotation_angle(self): x1, y1 = self.xy[0] x2, y2 = self.xy[1] angle = self.angle([x1, y1, x2, y2], [0,0,10,0]) * -1returnself.image.rotate(angle, expand=True)defangle(self, v1, v2): ...
获取旋转矩阵 double scale = 1.0; // 缩放比例 Mat rotationMatrix = cv2.GetRotationMatrix2D(center, angle, scale); // 应用旋转 Mat rotatedImage = new Mat(); cv2.WarpAffine(image, rotatedImage, rotationMatrix, image.Size); // 保存旋转后的图像 Cv2.ImWrite("rotated_input.jpg", rotated...
using OpenCvSharp;using PaddleOCRSharp;varimage=newMat("path_to_image.jpg");varangle=GetRotationAngle(image);// 计算旋转角度varrotatedImage=RotateImage(image,angle);// 使用PaddleOCR进行识别varocr=newPaddleOCR();ocr.Initialize(modelPath:@"path_to_model");varresult=ocr.Recognize(rotatedImage); ...
time def pdf2png(pdfPath, imgPath, zoom_x=2, zoom_y=2, rotation_angle=0): ''' # 将PDF转化为图片 pdfPath pdf文件的路径 imgPath 图像要保存的文件夹 zoom_x x方向的缩放系数 zoom_y y方向的缩放系数 rotation_angle 旋转角度 ''' time_start = time.time() # 打开PDF文件 pdf = fitz.ope...
前面文章说了ocr_rec.cpp里面是识别的方法,里面通过RunOCR函数进入,其中GetRotateCropImage的函数,用于处理生成的boxes的矩形点,然后截图这里面的图形进行OCR识别的。 在不动原来的GetRotateCropImage函数方法,我们再重写一个GetRotateCropImage,加入一个cv::Rect的参数用于生成截取的矩形。 代码语言:javascript 代码运行...
image = self.rotation_angle() box = image.getbbox() return image.crop(box) def rotation_angle(self): x1, y1 = self.xy[0] x2, y2 = self.xy[1] angle = self.angle([x1, y1, x2, y2], [0, 0, 10, 0]) * -1 return self.image.rotate(angle, expand=True) def angle(self...