def check_file(file_path):
with open(file_path) as f:
data = json.loads(f.read())
rects = [s["points"] for s in data["shapes"]]
labels = [s["label"] for s in data["shapes"]]
n = 0
for i, lbl in enumerate(labels):
try:
lt.human_label_to_int(lbl)
except Exception as e:
print(file_path)
print(e)
print(lbl, rects[i])
def string_to_line(text_line):
'''
:param text_line: single line text
:return: Line (not postprocessed)
'''
ext_mode = False
line = None
spaces_before = 0
for ch in text_line:
if ch == '~':
if not ext_mode:
ext_mode = True
ext_ch = ''
ch = None
else:
ext_mode = False
if ext_ch.isdigit():
ext_ch = '~'+ext_ch
ch = ext_ch
if ch:
if ext_mode:
ext_ch += ch
else:
if ch == ' ':
spaces_before += 1
else:
label = lt.human_label_to_int(ch)
if line is None:
line = Line(box=[0,0,0,0], label=label)
else:
line.chars.append(LineChar(box=[0,0,0,0], label=label))
line.chars[-1].spaces_before = spaces_before
spaces_before = 0
assert not ext_mode, text_line
return line
def read_LabelMe_annotation(label_filename, get_points):
'''
Reads LabelMe (see https://github.com/IlyaOvodov/labelme labelling tool) annotation JSON file.
:param label_filename: path to LabelMe annotation JSON file
:return: list of rect objects. Each rect object is a tuple (left, top, right, bottom, label) where
left..bottom are in [0,1), label is int in [1..63]
'''
if get_points:
raise NotImplementedError(
"read_annotation get_point mode not implemented for LabelMe annotation"
)
with open(label_filename, 'r', encoding='cp1251') as opened_json:
loaded = json.load(opened_json)
convert_x = limiting_scaler(loaded["imageWidth"], 1.0)
convert_y = limiting_scaler(loaded["imageHeight"], 1.0)
rects = [(
convert_x(min(xvals)),
convert_y(min(yvals)),
convert_x(max(xvals)),
convert_y(max(yvals)),
lt.human_label_to_int(label),
) for label, xvals, yvals in ((shape["label"],
[coords[0] for coords in shape["points"]],
[coords[1] for coords in shape["points"]])
for shape in loaded["shapes"])]
return rects