def downsized_hough(originals, images):
downsized = functions.process_several(
originals,
function=reshape.standard_resize,
new_width=200.0,
return_ratio=False
) # breaking because now returning ratio from std. resize
processed_downsized = functions.process_several(
downsized, function=functions.downsized_text_edging)
rotated_images = functions.draw_several(
processed_downsized,
drawing_images=downsized,
function=prob_hough_rotation) # downsize -> process -> Hough
return rotated_images
def hough_fullsized(images):
processed = functions.process_several(images,
function=functions.text_edging)
rotated_images = functions.draw_several(processed,
drawing_images=originals,
function=prob_hough_rotation)
return rotated_images
def hough_downsized(originals, images):
downsized = functions.process_several(originals,
function=reshape.standard_resize)
processed = functions.process_several(images,
function=functions.text_edging)
downsized_processed = functions.process_several(
processed,
function=reshape.standard_resize,
new_width=200.0,
return_ratio=False)
# rotated_images = functions.draw_several(downsized_processed, drawing_images = downsized_processed, function = prob_hough_rotation)
rotated_images = functions.draw_several2(
downsized_processed,
drawing_images=downsized_processed,
function=prob_hough)
functions.plot_images(rotated_images)
return rotated_images
def downsized_canny_dilated(image):
downsized, ratio = functions.standard_resize(image)
edged, titles = canny(downsized)
originals = utility.image_array(downsized, array_length = len(edged))
kernel = np.ones((5,5),np.uint8) # original was 15x15. 5x5 is working well right now.
dilated = functions.process_several(images = edged, function = cv2.dilate, kernel = kernel)
detected = functions.draw_several(images = dilated, drawing_images = originals, function = demo.vanilla_box_drawing)
functions.plot_images(dilated, titles)
functions.plot_images(detected,titles)
def downsized_canny_CI(image):
downsized, ratio = functions.standard_resize(image, new_width = 250.0)
# edged, titles = canny_thresh(downsized)
edged, titles = canny(downsized)
originals = utility.image_array(downsized, array_length = len(edged))
closed_inverted = functions.process_several(images = edged, function = functions.closed_inversion)
# detected = functions.process_several(images = closed_inverted, function = demo.vanilla_boxing)
detected = functions.draw_several(images = closed_inverted, drawing_images = originals, function = demo.vanilla_box_drawing)
functions.plot_images(edged,titles)
# functions.plot_images(closed_inverted, titles)
functions.plot_images(detected,titles)
def canny_comparison(image):
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
canny = cv2.Canny(blurred, threshold1 = 0, threshold2 = 40, apertureSize=3)
l2_canny = cv2.Canny(blurred, threshold1 = 0, threshold2 = 80, apertureSize=3 , L2gradient=False)
# l2_canny = cv2.Canny(blurred, threshold1 = 0, threshold2 = 80, apertureSize=3)
canny2 = cv2.Canny(blurred, threshold1 = 0, threshold2 = 100, apertureSize=3)
l2_canny2 = cv2.Canny(blurred, threshold1 = 0, threshold2 = 160, apertureSize=3 , L2gradient=False)
canny3 = cv2.Canny(blurred, threshold1 = 75, threshold2 = 200, apertureSize=3, L2gradient=False)
canny4 = cv2.Canny(blurred, threshold1 = 0, threshold2 = 200, apertureSize=3)
kernel = np.ones((5,5),np.uint8) # original was 15x15. 5x5 is working well right now.
dilated_canny = cv2.dilate(canny, kernel, iterations=1)
edged = [gray, canny, l2_canny, canny2, l2_canny2, canny3, canny4]
dilated = functions.process_several(images = edged, function = cv2.dilate, kernel = kernel)
# dilated_l2 = cv2.dilate(l2_canny, kernel, iterations=1)
# functions.plot_images([gray, dilated_canny, dilated_l2, canny2, l2_canny2])
functions.plot_images(dilated)
# files = ["pics/forms/E-Ticketing.png", "pics/indoor_720.jpg", "pics/forms/sample4_2.jpg"]
# files = utility.filenames_at_path("/media/thor/LEXAR/sampleDataset/input_sample", ".jpg") # hough threshold of 30 is best here
# files = utility.filenames_at_path("/home/thor/code/sr_project/pics/forms", ".jpg")
originals, images = utility.image_reading(files[:20])
for image in images:
detection(image.copy())
# text_region_method(image.copy())
# downsized_text_blobbing(image.copy())
originals, images = utility.image_reading(files)
# results = functions.process_several(images, function = pipeline)
# results = functions.process_several(images, function = downsized_text_blobbing)
results = functions.process_several(images, function=text_region_method)
functions.plot_images(results, files)
# text_region_method2(image)
# text_region_method(image)
# downsized_text_blobbing(image)
# canny_comparison(image)
# dilation_canny(image)
# rotate(image, 20)
# occlusion_demo(image)
# original_demo(image)
hull_attempt(image)
# alternate_rect_attempt(image)
def morph_comparison(image):
return 2
if __name__ == '__main__':
# image = cv2.imread(sys.argv[1])
# orig = image.copy()
# image = functions.standard_resize(image, new_width = 1000.0)
# edged = functions.text_edging(image)
# edged = functions.page_edging(image)
# downsized, _ = functions.standard_resize(edged, new_width = 100.0)
# functions.plot_images([downsized])
# downsized, _ = functions.standard_resize(image, new_width = 100.0)
# canny_comparison(downsized)
files = ["pics/demo/IMAG0603.jpg", "pics/demo/IMAG0604.jpg", "pics/demo/IMAG0605.jpg", "pics/demo/IMAG0606.jpg", "pics/demo/IMAG0607.jpg", "pics/demo/IMAG0608.jpg", "pics/demo/IMAG0611.jpg", "pics/demo/IMAG0612.jpg"]
# files = ["pics/forms/sample5.jpg", "pics/forms/sample2.jpg", "pics/forms/sample3.jpg", "pics/forms/sample4_4.jpg", "pics/forms/sample9.jpg", "pics/forms/sample11.jpg", "pics/forms/sample8.jpg", "pics/forms/sample12.jpg"]
# files = ["pics/forms/sample5.jpg", "pics/forms/sample2.jpg", "pics/forms/sample4_4.jpg", "pics/forms/sample11.jpg", "pics/forms/sample12.jpg", "pics/forms/sample10.jpg"]
originals, images = utility.image_reading(files)
# res = functions.process_several(images,downsized_canny)
# res = functions.process_several(images,downsized_canny_finetune)
# res = functions.process_several(images,downsized_canny_dilated)
res = functions.process_several(images,downsized_canny_CI)
# res = functions.process_several(images,downsized_canny_detection)
# result = functions.process_several()
