36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
import numpy as np
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import argparse
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import imutils
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import cv2
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import matplotlib.pyplot as plt
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import torch
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from PIL import Image
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path = "test1.jpg"
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img = cv2.imread(path)
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img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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img_gray = cv2.GaussianBlur(img_gray, (5, 5), 0)
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ret, im_th = cv2.threshold(img_gray, 90, 255, cv2.THRESH_BINARY_INV)
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ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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rects = [cv2.boundingRect(ctr) for ctr in ctrs]
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for rect in rects:
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# Draw the rectangles
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cv2.rectangle(img, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] + rect[3]), (0, 255, 0), 3)
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# Make the rectangular region around the digit
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leng = int(rect[3] * 1.6)
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pt1 = int(rect[1] + rect[3] // 2 - leng // 2)
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pt2 = int(rect[0] + rect[2] // 2 - leng // 2)
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roi = im_th[pt1:pt1+leng, pt2:pt2+leng]
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# Resize the image
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roi = cv2.resize(roi, (28, 28), interpolation=cv2.INTER_AREA)
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roi = cv2.dilate(roi, (3, 3))
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# Calculate the HOG features
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cv2.imshow("Resulting Image with Rectangular ROIs", img)
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cv2.waitKey() |