# patches for this file
patches = []
patch_labels = []
label_img = scipy.misc.imread(labels)
image_path = os.path.join('samples', os.path.basename(labels))
image, = metaomr.open(image_path)
staffsize.staffsize(image)
assert image.staff_dist >= 8
image_scale = 8.0 / image.staff_dist
image = scipy.misc.imresize(
image.byteimg[:image.orig_size[0], :image.orig_size[1]].astype(bool),
image_scale,
interp='nearest')
num_label_patches = 0
for label_type, label_name in COLOR_LABELS.iteritems():
our_patches = []
our_patch_labels = []
is_label = label_img[:, :, :3] == np.array([[label_type]])
# When scaling down, need to ensure each label pixel maps to some
# new pixel and isn't overwritten by the background
label_y, label_x = np.where(is_label.all(axis=-1))
if len(label_y):
label_y = (label_y * image_scale).astype(int)
label_x = (label_x * image_scale).astype(int)
scale_label = np.zeros_like(image)
scale_label[label_y, label_x] = 1
size = LABEL_SIZE
if label_name in object_size:
size = object_size[label_name]
if size > 1:
for line in open('unlabeled_patches').readlines():
patch_str = line.strip()
if patch_str in already_labeled:
continue
img_patch = np.array(list(patch_str),int).reshape((35,35))
patch = np.empty((35, 35, 3), np.uint8)
patch[:] = np.where(img_patch, 0, 255)[:,:,None]
patch[c-5:c+6,c,0] ^= 0xFF
patch[c,c-5:c+6,0] ^= 0xFF
patch[c-1:c+2, c-1:c+2, 1] ^= 0xFF
yield img_patch, patch
os.unlink('unlabeled_patches')
t=Tk()
classes = ["background"] + sorted(COLOR_LABELS.values()) + ['skip','quit']
patches_f = open('patches.csv', 'a')
patch = None
gen = get_images()
label = Label(t)
label.grid(row=0, column=0, rowspan=len(classes))
buttons = dict()
def button(x):
global real_img, patch, img, imgTk
if x == 'skip':
pass
elif x == 'quit':
sys.exit(0)
elif x is not None:
print x
vals = map(str, (real_img != 0).ravel().astype(int))
# patches for this file
patches = []
patch_labels = []
label_img = scipy.misc.imread(labels)
image_path = os.path.join('samples', os.path.basename(labels))
image, = metaomr.open(image_path)
staffsize.staffsize(image)
assert image.staff_dist >= 8
image_scale = 8.0 / image.staff_dist
image = scipy.misc.imresize(image.byteimg[:image.orig_size[0],
:image.orig_size[1]].astype(bool),
image_scale,
interp='nearest')
num_label_patches = 0
for label_type, label_name in COLOR_LABELS.iteritems():
our_patches = []
our_patch_labels = []
is_label = label_img[:, :, :3] == np.array([[label_type]])
# When scaling down, need to ensure each label pixel maps to some
# new pixel and isn't overwritten by the background
label_y, label_x = np.where(is_label.all(axis=-1))
if len(label_y):
label_y = (label_y * image_scale).astype(int)
label_x = (label_x * image_scale).astype(int)
scale_label = np.zeros_like(image)
scale_label[label_y, label_x] = 1
size = LABEL_SIZE
if label_name in object_size:
size = object_size[label_name]
if size > 1:
