def find_possible_chars_in_scene(img_thresh) -> [PossibleChar]:
list_of_possible_chars: [PossibleChar] = []
int_count_of_possible_chars: int = 0
img_thresh_copy = img_thresh.copy()
contours, npa_hierarchy = cv2.findContours(img_thresh_copy, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
height, width = img_thresh.shape
img_contours = np.zeros((height, width, 3), np.uint8)
for i in range(0, len(contours)):
if not SUPER_SPEED_MODE:
cv2.drawContours(img_contours, contours, i, SCALAR_WHITE, 3)
possible_char = PossibleChar.PossibleChar(contours[i])
if DetectChars.check_if_possible_char(possible_char):
int_count_of_possible_chars = int_count_of_possible_chars + 1
list_of_possible_chars.append(possible_char)
if NO_ERROR_PRINT_ENABLED:
print("\n[F:Find Possible Chars in Scene] - len(contours) = " + str(len(contours)))
print("\n[F:Find Possible Chars in Scene] - int_count_of_possible_chars = " + str(int_count_of_possible_chars))
if SHOW_IMAGE:
cv2.imshow("[F:Find Possible Chars in Scene] - Contours", img_contours)
if SAVE_IMAGE:
cv2.imwrite("./output/showImage/4-Find Possible Chars-Contours.jpg", img_contours)
return list_of_possible_chars
def find_possible_chars_in_scene(img_thresh):
list_of_possible_chars = []
count_of_possible_chars = 0
img_thresh_copy = img_thresh.copy()
img_contours, contours, hierarchy = cv2.findContours(
img_thresh_copy, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
height, width = img_thresh.shape
img_contours = np.zeros((height, width, 3), np.uint8)
for i in range(0, len(contours)):
if PlateRecognition.showSteps:
cv2.drawContours(img_contours, contours, i,
PlateRecognition.SCALAR_WHITE)
possible_char = PossibleChar.PossibleChar(contours[i])
if DetectChars.check_if_possible_char(possible_char):
count_of_possible_chars = count_of_possible_chars + 1
list_of_possible_chars.append(possible_char)
return list_of_possible_chars
