def resize_to_cell_size(the_ragion, interpolation = cv2.INTER_AREA):
# the_ragion.shape.pl()
heighted_ragion = Image.resize_keeping_ratio_by_fixed_length(the_ragion, IMG_SIZE, interpolation)
# heighted_ragion.shape.pl()
standard_ragion = Ragion.fill(heighted_ragion,(IMG_SIZE,IMG_SIZE))
# standard_ragion.shape.pl()
return standard_ragion
def identify_wrong_number(number_ragions, difference, show_actual=True):
all_number_images = generate_number_images()
identified_number_ragions = number_ragions[:]
for index,_,actual in difference:
height, width = number_ragions[index].shape
if show_actual:
number_ragions[index] = Image.resize_keeping_ratio_by_height(all_number_images[actual], height)
height, width = number_ragions[index].shape
identified_number_ragions[index] = Ragion.fill(number_ragions[index], (height+2, width+2), 1)
return identified_number_ragions
def adjust_one(the_ragion):
# the_ragion = cv2.GaussianBlur(the_ragion, ksize=(5,5), sigmaX=0)
# blockSize = the_ragion.shape[1]/2
# if blockSize % 2 == 0:
# blockSize += 1
# thresholded_ragion = cv2.adaptiveThreshold(the_ragion,WHITE,
# cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY_INV, blockSize=blockSize, C=2)
# thresholded_ragion = Image.threshold_white_with_mean_percent(the_ragion, 0.70)
threshold_value = Ragion.cal_threshold_value(the_ragion, square_ragion, 0.70)
thresholded_ragion = Image.threshold_white(the_ragion, threshold_value)
return thresholded_ragion
def resize_to_cell_size(the_ragion):
heighted_ragion = resize_keeping_ratio_by_height(the_ragion, IMG_SIZE)
standard_ragion = Ragion.fill(heighted_ragion, (IMG_SIZE, IMG_SIZE))
return standard_ragion
# # Display.image(gray_image)
with test("get clear number ragion"):
som_svm = MultipleSvm.load_variables(Smo, data_file_helper.SUPPLEMENT_RESULT_PATH)
file_path = Resource.get_test_path("sample_15_null_38_image.jpg")
the_ragion = cv2.imread(file_path, 0)
# the_ragion.mean().ppl()
# the_ragion.ppl()
# thresholded_ragion = Image.threshold_white_with_mean_percent(the_ragion, 0.8)
# thresholded_ragion.ppl()
# Display.image(thresholded_ragion)
file_path = Resource.get_test_path("sample_15_square.jpg")
square_ragion = cv2.imread(file_path, 0)
# square_ragion.mean().ppl()
threshold_value = Ragion.cal_threshold_value(the_ragion, square_ragion, 0.69)
thresholded_ragion = Image.threshold_white(the_ragion, threshold_value)
# thresholded_ragion = cv2.adaptiveThreshold(the_ragion, 255,
# cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY_INV, blockSize=7, C=2)
cell_rect = nonzero_rect.analyze_from_center(thresholded_ragion)
if cell_rect:
cell_ragion = Rect.get_ragion(cell_rect, thresholded_ragion)
cell_rect.pl()
# Display.image(cell_ragion)
file_path = Resource.get_test_path("sample_19_07_05_image.jpg")
the_ragion = cv2.imread(file_path, 0)
# the_ragion.mean().ppl()
file_path = Resource.get_test_path("sample_19_square.jpg")
square_ragion = cv2.imread(file_path, 0)