ret, th1 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY) ret, th2 = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY_INV) ret, th3 = cv2.threshold(img, 127, 255, cv2 ...
Image processing and computer vision play crucial roles in data science, allowing for the extraction of information from images. Basic image transformation techniques include translation, parametric ...
x1 = center_x+(radius-margin)*math.cos(i*6*np.pi/180.0) y1 = center_y+(radius-margin)*math.sin(i*6*np.pi/180.0) pt1.append((int(x1), int(y1))) # 同心小圆，计算 ...
In this tutorial, we build an Advanced OCR AI Agent in Google Colab using EasyOCR, OpenCV, and Pillow, running fully offline with GPU acceleration. The agent includes a preprocessing pipeline with ...
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