23 lines
757 B
Python
23 lines
757 B
Python
import cv2 as cv
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cvNet = cv.dnn.readNetFromTensorflow('frozen_inference_graph.pb', 'graph.pbtxt')
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img = cv.imread('IMG_0825.jpg')
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img = cv.resize(img, None, fx=0.1, fy=0.1, interpolation = cv.INTER_AREA)
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rows = img.shape[0]
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cols = img.shape[1]
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print(str(rows) + " " + str(cols))
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cvNet.setInput(cv.dnn.blobFromImage(img, size=(300, 300), swapRB=True, crop=False))
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cvOut = cvNet.forward()
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for detection in cvOut[0,0,:,:]:
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score = float(detection[2])
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if score > 0.6:
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left = detection[3] * cols
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top = detection[4] * rows
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right = detection[5] * cols
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bottom = detection[6] * rows
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cv.rectangle(img, (int(left), int(top)), (int(right), int(bottom)), (23, 230, 210), thickness=2)
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cv.imshow('img', img)
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cv.waitKey() |