def segmap(image):
'''
return: uint8 mask image, bg=black.
If image is not float32 nor bgr-3channel image, convert it.
But snet input img(float32) pixel range: 0 ~ 1 is mandatory.
'''
def assert_img_range(img):
assert (1.0 >= img).all(), img.max()
assert (img >= 0.0).all(), img.min()
return img
def decategorize(mask):
return iu.decategorize(mask, iu.rgb2wk_map)
with tf.Session() as sess:
snet_in = consts.snet_in('0.1.0', sess)
snet_out = consts.snet_out('0.1.0', sess)
def snet(img):
return sess.run(snet_out, feed_dict={snet_in: img})
return fp.go(
image,
iu.channel3img,
iu.float32, # preprocess
assert_img_range,
lambda img: segment(snet, img),
iu.map_max_row,
decategorize,
iu.uint8, # postprocess
)
def imgpath2mask(imgpath):
return fp.go(
imgpath,
lambda path: io.load(path, io.NDARR),
core.segmap,
io.segmap2mask
)
def gen_mask_all(self):
imgpath = state.now_image()
if imgpath is None: return None
mask = fp.go(imgpath, lambda path: io.load(path, io.NDARR),
core.segmap, io.segmap2mask)
io.save(state.now_mask(), mask)
self.update_gui()
return mask
def mask2segmap(mask):
'''
convert mask(gui, file) to segmap(snet output)
mask: np.uint8, bgra, {fg=red, bg=transparent}
segmap: np.uint8, bgr, b=g=r {fg=white, bg=black}
'''
return fp.go(mask,
lambda m4: np.sum(m4[:, :, :3], axis=-1, dtype=np.uint8),
lambda m1: np.expand_dims(m1, axis=-1), lambda m1: cv2.merge(
(m1, m1, m1)))
def test_gen_mask():
open_project('./fixture/real_proj/')
expected = fp.go(
'./fixture/real_proj/images/bgr1.png',
cv2.imread, core.segmap, io.segmap2mask
)
main_window.gen_mask()
actual = cv2.imread(
'./fixture/real_proj/masks/bgr1.png',
cv2.IMREAD_UNCHANGED) #NOTE: rgba -> 4channel, wb -> 1ch..
assert np.array_equal(actual, expected)
def set_project(prj_dirpath):
assert Path(prj_dirpath, config.IMGDIR).exists()
assert Path(prj_dirpath, config.MASKDIR).exists()
global img_paths, mask_paths, _cursor
img_paths = fp.go(
Path(prj_dirpath) / config.IMGDIR, fu.children,
fp.filter(iu.is_img_file), fu.human_sorted, tuple)
mask_paths = tuple(
fp.map(
fp.pipe(fu.replace1(config.IMGDIR, config.MASKDIR), Path,
lambda p: p.with_suffix('.png'), str), img_paths))
_cursor = 0
def set_project(prj_dirpath):
assert Path(prj_dirpath, consts.IMGDIR).exists()
assert Path(prj_dirpath, consts.MASKDIR).exists()
assert Path(prj_dirpath, consts.PREV_IMGDIR).exists()
assert Path(prj_dirpath, consts.PREV_MASKDIR).exists()
global img_paths, mask_paths,\
prev_img_paths, prev_mask_paths, _cursor
img_paths = fp.go(
Path(prj_dirpath) / consts.IMGDIR,
fu.children,
fp.filter(iu.is_img_file),
fu.human_sorted,
fp.map(lambda pstr: pstr.replace('\\','/')),
tuple
)
mask_paths = tuple(fp.map(
fp.pipe(
fu.replace1(consts.IMGDIR, consts.MASKDIR),
Path,
lambda p:p.with_suffix('.png'),
str,
lambda pstr: pstr.replace('\\','/')
),
img_paths
))
prev_img_paths = tuple(fp.map(
fu.replace1(consts.IMGDIR, consts.PREV_IMGDIR),
img_paths
))
prev_mask_paths = tuple(fp.map(
fu.replace1(consts.MASKDIR, consts.PREV_MASKDIR),
mask_paths
))
_cursor = 0
