import cv2
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import numpy as np
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import pandas as pd
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if __name__ == '__main__':
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# img_test = cv2.imread('data/rtr-174-jarad-golgari-lich-lord.jpg')
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# img_test = cv2.imread('data/cn2-78-queen-marchesa.png')
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img_test = cv2.imread('data/c16-143-burgeoning.png')
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# img_test = cv2.imread('data/li38_handOfCards.jpg')
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# img_test = cv2.imread('data/pro_tour_side.png')
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img_gray = cv2.cvtColor(img_test, cv2.COLOR_BGR2GRAY)
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_, img_thresh = cv2.threshold(img_gray, 50, 255, cv2.THRESH_BINARY)
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# cv2.imshow('original', img_test)
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cv2.imshow('threshold', img_thresh)
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kernel = np.ones((7, 7), np.uint8)
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img_dilate = cv2.dilate(img_thresh, kernel, iterations=1)
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# img_erode = cv2.erode(img_thresh, kernel, iterations=1)
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# img_open = cv2.morphologyEx(img_thresh, cv2.MORPH_OPEN, kernel)
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img_close = cv2.morphologyEx(img_thresh, cv2.MORPH_CLOSE, kernel)
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cv2.imshow('dilated', img_dilate)
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# cv2.imshow('eroded', img_erode)
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# cv2.imshow('opened', img_open)
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# cv2.imshow('closed', img_close)
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img_edge = cv2.Canny(img_dilate, 100, 200)
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cv2.imshow('edge', img_edge)
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lines = cv2.HoughLines(img_edge, 1, np.pi / 180, 200)
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if lines is not None:
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img_hough = cv2.cvtColor(img_dilate.copy(), cv2.COLOR_GRAY2BGR)
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for line in lines:
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rho, theta = line[0]
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a = np.cos(theta)
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b = np.sin(theta)
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x0 = a * rho
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y0 = b * rho
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x1 = int(x0 + 1000 * (-b))
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y1 = int(y0 + 1000 * (a))
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x2 = int(x0 - 1000 * (-b))
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y2 = int(y0 - 1000 * (a))
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cv2.line(img_hough, (x1, y1), (x2, y2), (0, 0, 255), 2)
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cv2.imshow('hough', img_hough)
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else:
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print('Hough couldn\'t find any lines')
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'''
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lines = cv2.HoughLinesP(img_edge, 1, np.pi / 180, 200, 50, 100)
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if lines is not None:
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img_hough = cv2.cvtColor(img_dilate.copy(), cv2.COLOR_GRAY2BGR)
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for line in lines:
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x1, y1, x2, y2 = line[0]
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cv2.line(img_hough, (x1, y1), (x2, y2), (0, 0, 255), 3)
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cv2.imshow('hough', img_hough)
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else:
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print('Hough couldn\'t find any lines')
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img_contour, contours, hierchy = cv2.findContours(img_dilate, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
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img_contour = cv2.cvtColor(img_contour, cv2.COLOR_GRAY2BGR)
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if len(contours) > 0:
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cv2.drawContours(img_contour, contours, -1, (0, 0, 255), 1)
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cv2.imshow('contours', img_contour)
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'''
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cv2.waitKey(0
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