Page 270 - MDP2020-1

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# insert to dict
contours_dict.append({
'contour': contour,
'x': x,
'y': y,
'w': w,
'h': h,
'cx': x + (w / 2),
'cy': y + (h / 2)
})
plt.figure(figsize=(12, 10))
plt.imshow(temp_result, cmap='gray')
MIN_AREA = 80
MIN_WIDTH, MIN_HEIGHT = 2, 8
MIN_RATIO, MAX_RATIO = 0.25, 1.0
possible_contours = []
cnt = 0
for d in contours_dict:
area = d['w'] * d['h']
ratio = d['w'] / d['h']

if area > MIN_AREA \
and d['w'] > MIN_WIDTH and d['h'] > MIN_HEIGHT \
and MIN_RATIO < ratio < MAX_RATIO:
d['idx'] = cnt
cnt += 1
possible_contours.append(d)

# visualize possible contours
temp_result = np.zeros((height, width, channel), dtype=np.uint8)
for d in possible_contours:
# cv2.drawContours(temp_result, d['contour'], -1, (255, 255, 255))
cv2.rectangle(temp_result, pt1=(d['x'], d['y']), pt2=(d['x']+d['w'], d['y']+d['h']), color=(255,
255, 255), thickness=2)
plt.figure(figsize=(12, 10))
plt.imshow(temp_result, cmap='gray')
MAX_DIAG_MULTIPLYER = 5 # 5
MAX_ANGLE_DIFF = 12.0 # 12.0
MAX_AREA_DIFF = 0.5 # 0.5
MAX_WIDTH_DIFF = 0.8
MAX_HEIGHT_DIFF = 0.2
MIN_N_MATCHED = 3 # 3
def find_chars(contour_list):
matched_result_idx = []