import cv2
import image_utils
for i in range(0, 10):
video = cv2.VideoCapture('test samples/video-' + str(i) + '.avi')
if video.isOpened() == 0:
print("Error!!!")
idx = 0
while video.isOpened():
ret, frame = video.read()
if ret:
removed_noise_frame = image_utils.image_bin(image_utils.image_gray(frame), 200)
removed_noise_frame = image_utils.erode(image_utils.dilate(removed_noise_frame))
cv2.imwrite('noiseless_videos/video_' + str(i) + '/frame_' + str(idx) + '.jpg', removed_noise_frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
print(idx)
idx = idx + 1
video.release()
img_green = line_utils.get_only_line(1, frame.copy())
lines_blue = line_utils.get_line(img_blue)
lines_green = line_utils.get_line(img_green)
#img_bin = image_utils.erode_large(image_utils.dilate_large(img)) #dodata spolj dilatacija
#sa dvostruke spolj dil promenjeno na bez spolj dil
#ovde je bilo umesto frame img_bin, da vidimo kakve cu rez dobiti sa ovim
lines_blue_pixels = line_utils.convert_lines_to_pixels(
lines_blue, image_utils.image_gray(frame))
lines_green_pixels = line_utils.convert_lines_to_pixels(
lines_green, image_utils.image_gray(frame))
img_bin = image_utils.image_bin(image_utils.image_gray(frame),
200)
img_bin_ed = image_utils.dilate(
image_utils.erode(image_utils.dilate(img_bin, 1), 1), 2)
cv2.imwrite(
'noiseless_videos/video_' + str(i) + '/frame_' + str(idx) +
'.jpg', img_bin_ed)
selected_regions, numbers, dimensions = video_utils.select_roi(
frame.copy(), img_bin_ed, idx, i)
blue_regions, blue_dimensions = line_utils.check_close_ones(
numbers, dimensions, lines_blue_pixels, i)
green_regions, green_dimensions = line_utils.check_close_ones(
numbers, dimensions, lines_green_pixels, i)
v_h = int(video.get(4))
print(v_w)
print(v_h)
new_video = cv2.VideoWriter('test samples/video_gr-' + str(i) + '.avi',
cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 40,
(v_w, v_h))
idx = 0
while video.isOpened():
ret, frame = video.read()
if ret:
img = image_utils.image_bin(image_utils.image_gray(frame))
img_bin = image_utils.erode(image_utils.dilate(img))
selected_regions, numbers = video_utils.select_roi(
frame.copy(), img_bin, idx, i)
cv2.imwrite(
"contoured_frames/video_" + str(i) + "/frame_" + str(idx) +
".jpg", selected_regions)
new_video.write(selected_regions)
cv2.imshow("Video" + str(i), selected_regions)
idx = idx + 1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
import image_utils
import training_utils
import numpy as np
image_color = image_utils.load_image('test samples/test_samples(0,25).png')
img = image_utils.image_bin(image_utils.image_gray(image_color))
img_bin = image_utils.erode(image_utils.dilate(img))
alphabet = []
selected_regions, numbers, alphabet = image_utils.select_roi(
image_color.copy(), img, alphabet)
image_utils.display_image(selected_regions)
print(alphabet)
inputs = image_utils.prepare_for_ann(numbers)
outputs = training_utils.convert_output(alphabet)
ann = training_utils.load_modell()
#print(outputs)
result = ann.predict(np.array(inputs, np.float32))
final_alphabet = training_utils.convert_output([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
print(result)
print(training_utils.display_result(result, final_alphabet, alphabet))