58 lines
1.6 KiB
Python
58 lines
1.6 KiB
Python
import numpy as np
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import argparse
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import cv2
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from photoAnalysisUtils import *
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def menuAnalyseIMG(url):
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result_vector = []
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img_tested = url
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image = img_tested
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blurred = cv2.GaussianBlur(image, (5, 5), 0)
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edged = cv2.Canny(blurred, 20, 50)
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height = image.shape[0]
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width = image.shape[1]
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referencePoint = open("referencePoint.txt", "r")
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checkBoxesCords = open("checkBoxesCords.txt", "r")
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referencePoint = referencePoint.readlines()
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checkBoxesCords = checkBoxesCords.readlines()
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for corners in referencePoint:
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template_x, template_y = corners.split()
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image, x, y = searchReferencePointCorner(image)
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offsetX = int(template_x) - x
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offsetY = int(template_y) - y
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i=1
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for checkBox in checkBoxesCords:
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x, y, w, h = checkBox.split()
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x = int(x) - offsetX
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y = int(y) - offsetY
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w = int(w)
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h = int(h)
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cv2.rectangle(image, (x, y), (x + w, y + h), (36, 255, 12), 2)
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crop_img = edged[y:y + h, x:x + w]
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n_white_pix = np.sum(crop_img == 255)
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n_black_pix = np.sum(crop_img == 0)
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if(n_white_pix+n_black_pix)*0.2 < n_white_pix:
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#print(str(i)+" FILL")
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result_vector.append([i, 1])
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else:
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#print(str(i)+" EMPTY")
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result_vector.append([i, 0])
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#print("White i ="+str(i)+" white = "+str(n_white_pix))
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#print("Black i ="+str(i)+" black = "+str(n_black_pix))
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#cv2.imwrite("maska"+str(i)+".jpg", crop_img)
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i = i+1
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cv2.imwrite("tested.jpg", image)
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return result_vector
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# img_tested = cv2.imread('orders/1.jpg')
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# menuAnalyseIMG(img_tested) |