def preprocess(image_fname, output_dir, image_size=768):
image = cv2.imread(image_fname)
image = crop_black(image, tolerance=5)
image = longest_max_size(image, max_size=image_size, interpolation=cv2.INTER_CUBIC)
image_id = fs.id_from_fname(image_fname)
dst_fname = os.path.join(output_dir, image_id + '.png')
cv2.imwrite(dst_fname, image)
return
def test_unsharp_mask():
for image_fname in [
'4_left.png', '35_left.png', '44_right.png', '68_right.png',
'92_left.png'
]:
image = cv2.imread(image_fname)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# image = A.CLAHE(always_apply=True)(image=image)['image']
image = crop_black(image, tolerance=5)
cropped = unsharp_mask(image)
f, ax = plt.subplots(1, 2)
ax[0].imshow(image)
ax[1].imshow(cropped)
f.show()
def test_brightness_and_contrast_auto():
for image_fname in [
'4_left.png', '35_left.png', '44_right.png', '68_right.png',
'92_left.png'
]:
image = cv2.imread(image_fname)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# image = A.CLAHE(always_apply=True)(image=image)['image']
image = crop_black(image, tolerance=5)
cropped = brightness_and_contrast_auto(image, 5)
f, ax = plt.subplots(1, 2)
ax[0].imshow(image)
ax[1].imshow(cropped)
f.show()
def test_crop_black_regions():
for image_fname in [
# 'data/train_images/0a4e1a29ffff.png',
# 'data/train_images/0a61bddab956.png',
# 'tests/19150_right.jpeg',
fs.auto_file('3704_left.jpeg', where='..')
]:
image = cv2.imread(image_fname)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# image = A.CLAHE(always_apply=True)(image=image)['image']
cropped = crop_black(image)
f, ax = plt.subplots(1, 2)
ax[0].imshow(image)
ax[1].imshow(cropped)
f.show()
def test_enchance_contrast_clahe():
for image_fname in [
'4_left.png', '35_left.png', '44_right.png', '68_right.png',
'92_left.png'
]:
image = cv2.imread(image_fname)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# image = A.CLAHE(always_apply=True)(image=image)['image']
image = crop_black(image)
cropped = clahe_preprocessing(image,
clip_limit=3,
tile_grid_size=(32, 32))
f, ax = plt.subplots(1, 2)
ax[0].imshow(image)
ax[1].imshow(cropped)
f.show()
def test_drop_red_channel():
for image_fname in [
'4_left.png', '35_left.png', '44_right.png', '68_right.png',
'92_left.png'
]:
image = cv2.imread(image_fname)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# image = A.CLAHE(always_apply=True)(image=image)['image']
image = crop_black(image, tolerance=5)
cropped = red_free(image)
median = cv2.medianBlur(image, ksize=15)
norm = cv2.addWeighted(image, 0.5, median, -0.5, 128)
# cropped[..., 0] = cv2.cvtColor(cropped, cv2.COLOR_BGR2GRAY)
f, ax = plt.subplots(1, 3)
ax[0].imshow(image)
ax[1].imshow(cropped)
ax[2].imshow(norm)
f.show()