def test_generate_trimap(self):
image = cv.imread('fg/1-1252426161dfXY.jpg')
alpha = cv.imread('mask/1-1252426161dfXY.jpg', 0)
trimap = generate_trimap(alpha)
self.assertEqual(trimap.shape, (615, 410))
# ensure np.where works as expected.
count = 0
h, w = trimap.shape[:2]
for i in range(h):
for j in range(w):
if trimap[i, j] == unknown_code:
count += 1
x_indices, y_indices = np.where(trimap == unknown_code)
num_unknowns = len(x_indices)
self.assertEqual(count, num_unknowns)
# ensure an unknown pixel is chosen
ix = random.choice(range(num_unknowns))
center_x = x_indices[ix]
center_y = y_indices[ix]
self.assertEqual(trimap[center_x, center_y], unknown_code)
x, y = random_choice(trimap)
# print(x, y)
image = safe_crop(image, x, y)
trimap = safe_crop(trimap, x, y)
alpha = safe_crop(alpha, x, y)
cv.imwrite('temp/test_generate_trimap_image.png', image)
cv.imwrite('temp/test_generate_trimap_trimap.png', trimap)
cv.imwrite('temp/test_generate_trimap_alpha.png', alpha)
def test_flip(self):
image = cv.imread('fg/1-1252426161dfXY.jpg')
# print(image.shape)
alpha = cv.imread('mask/1-1252426161dfXY.jpg', 0)
trimap = generate_trimap(alpha)
x, y = random_choice(trimap)
image = safe_crop(image, x, y)
trimap = safe_crop(trimap, x, y)
alpha = safe_crop(alpha, x, y)
image = np.fliplr(image)
trimap = np.fliplr(trimap)
alpha = np.fliplr(alpha)
cv.imwrite('temp/test_flip_image.png', image)
cv.imwrite('temp/test_flip_trimap.png', trimap)
cv.imwrite('temp/test_flip_alpha.png', alpha)
def test_resize(self):
name = '0_0.png'
filename = os.path.join('merged', name)
image = cv.imread(filename)
bg_h, bg_w = image.shape[:2]
a = get_alpha(name)
a_h, a_w = a.shape[:2]
alpha = np.zeros((bg_h, bg_w), np.float32)
alpha[0:a_h, 0:a_w] = a
trimap = generate_trimap(alpha)
# 剪切尺寸 320:640:480 = 3:1:1
crop_size = (480, 480)
x, y = random_choice(trimap, crop_size)
image = safe_crop(image, x, y, crop_size)
trimap = safe_crop(trimap, x, y, crop_size)
alpha = safe_crop(alpha, x, y, crop_size)
cv.imwrite('temp/test_resize_image.png', image)
cv.imwrite('temp/test_resize_trimap.png', trimap)
cv.imwrite('temp/test_resize_alpha.png', alpha)
filename = samples[i]
image_name = filename.split('.')[0]
print('\nStart processing image: {}'.format(filename))
bgr_img = cv.imread(os.path.join(out_test_path, filename))
bg_h, bg_w = bgr_img.shape[:2]
print('bg_h, bg_w: ' + str((bg_h, bg_w)))
a = get_alpha_test(image_name)
a_h, a_w = a.shape[:2]
print('a_h, a_w: ' + str((a_h, a_w)))
alpha = np.zeros((bg_h, bg_w), np.float32)
alpha[0:a_h, 0:a_w] = a
trimap = generate_trimap(alpha)
different_sizes = [(320, 320), (320, 320), (320, 320), (480, 480), (640, 640)]
crop_size = random.choice(different_sizes)
x, y = random_choice(trimap, crop_size)
print('x, y: ' + str((x, y)))
bgr_img = safe_crop(bgr_img, x, y, crop_size)
alpha = safe_crop(alpha, x, y, crop_size)
trimap = safe_crop(trimap, x, y, crop_size)
cv.imwrite('images/{}_image.png'.format(i), np.array(bgr_img).astype(np.uint8))
cv.imwrite('images/{}_trimap.png'.format(i), np.array(trimap).astype(np.uint8))
cv.imwrite('images/{}_alpha.png'.format(i), np.array(alpha).astype(np.uint8))
x_test = np.empty((1, img_rows, img_cols, 4), dtype=np.float32)
x_test[0, :, :, 0:3] = bgr_img / 255.
x_test[0, :, :, 3] = trimap / 255.
total_loss = 0.0
for i in range(len(samples)):
filename = samples[i]
image_name = filename.split('.')[0]
print('Start processing image: {}'.format(filename))
x_test = np.empty((1, img_rows, img_cols, 4), dtype=np.float32)
bgr_img = cv.imread(os.path.join(out_test_path, filename))
bg_h, bg_w = bgr_img.shape[:2]
print(bg_h, bg_w)
a = get_alpha_test(image_name)
a_h, a_w = a.shape[:2]
print(a_h, a_w)
alpha = np.zeros((bg_h, bg_w), np.float32)
alpha[0:a_h, 0:a_w] = a
trimap = generate_trimap(alpha)
different_sizes = [(320, 320), (320, 320), (320, 320), (480, 480), (640, 640)]
crop_size = random.choice(different_sizes)
x, y = random_choice(trimap, crop_size)
print(x, y)
bgr_img = safe_crop(bgr_img, x, y, crop_size)
alpha = safe_crop(alpha, x, y, crop_size)
trimap = safe_crop(trimap, x, y, crop_size)
cv.imwrite('images/{}_image.png'.format(i), np.array(bgr_img).astype(np.uint8))
cv.imwrite('images/{}_trimap.png'.format(i), np.array(trimap).astype(np.uint8))
cv.imwrite('images/{}_alpha.png'.format(i), np.array(alpha).astype(np.uint8))
x_test = np.empty((1, 320, 320, 4), dtype=np.float32)
x_test[0, :, :, 0:3] = bgr_img / 255.
x_test[0, :, :, 3] = trimap / 255.
