Update labelme2voc.py and labelme2coco.py accordingly

examples/instance_segmentation/labelme2coco.py

@@ -8,6 +8,7 @@
 import os
 import os.path as osp
 import sys
+import uuid
 
 import numpy as np
 import PIL.Image
@@ -111,21 +112,28 @@ def main():
  for shape in label_data['shapes']:
  points = shape['points']
  label = shape['label']
- shape_type = shape.get('shape_type', None)
+ group_id = shape.get('group_id')
+ shape_type = shape.get('shape_type')
  mask = labelme.utils.shape_to_mask(
  img.shape[:2], points, shape_type
  )
 
- if label in masks:
- masks[label] = masks[label] | mask
+ if group_id is None:
+ group_id = uuid.uuid1()
+
+ instance = (label, group_id)
+
+ if instance in masks:
+ masks[instance] = masks[instance] | mask
  else:
- masks[label] = mask
+ masks[instance] = mask
 
  points = np.asarray(points).flatten().tolist()
- segmentations[label].append(points)
+ segmentations[instance].append(points)
+ segmentations = dict(segmentations)
 
- for label, mask in masks.items():
- cls_name = label.split('-')[0]
+ for instance, mask in masks.items():
+ cls_name, group_id = instance
  if cls_name not in class_name_to_id:
  continue
  cls_id = class_name_to_id[cls_name]
@@ -139,7 +147,7 @@ def main():
  id=len(data['annotations']),
  image_id=image_id,
  category_id=cls_id,
- segmentation=segmentations[label],
+ segmentation=segmentations[instance],
  area=area,
  bbox=bbox,
  iscrowd=0,

examples/instance_segmentation/labelme2voc.py

@@ -103,7 +103,6 @@ def main():
  img_shape=img.shape,
  shapes=data['shapes'],
  label_name_to_value=class_name_to_id,
- type='instance',
  )
  ins[cls == -1] = 0 # ignore it.
 

examples/semantic_segmentation/labelme2voc.py

@@ -81,7 +81,7 @@ def main():
  f.write(label_file.imageData)
  img = labelme.utils.img_data_to_arr(label_file.imageData)
 
- lbl = labelme.utils.shapes_to_label(
+ lbl, _ = labelme.utils.shapes_to_label(
  img_shape=img.shape,
  shapes=label_file.shapes,
  label_name_to_value=class_name_to_id,

labelme/cli/draw_json.py

@@ -41,7 +41,9 @@ def main():
  else:
  label_value = len(label_name_to_value)
  label_name_to_value[label_name] = label_value
- lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)
+ lbl, _ = utils.shapes_to_label(
+ img.shape, data['shapes'], label_name_to_value
+ )
 
  label_names = [None] * (max(label_name_to_value.values()) + 1)
  for name, value in label_name_to_value.items():

labelme/cli/json_to_dataset.py

@@ -50,7 +50,9 @@ def main():
  else:
  label_value = len(label_name_to_value)
  label_name_to_value[label_name] = label_value
- lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)
+ lbl, _ = utils.shapes_to_label(
+ img.shape, data['shapes'], label_name_to_value
+ )
 
  label_names = [None] * (max(label_name_to_value.values()) + 1)
  for name, value in label_name_to_value.items():

labelme/utils/shape.py

@@ -1,4 +1,5 @@
 import math
+import uuid
 
 import numpy as np
 import PIL.Image
@@ -46,33 +47,31 @@ def shape_to_mask(img_shape, points, shape_type=None,
  return mask
 
 
-def shapes_to_label(img_shape, shapes, label_name_to_value, type='class'):
- assert type in ['class', 'instance']
-
+def shapes_to_label(img_shape, shapes, label_name_to_value):
  cls = np.zeros(img_shape[:2], dtype=np.int32)
- if type == 'instance':
- ins = np.zeros(img_shape[:2], dtype=np.int32)
- instance_names = ['_background_']
+ ins = np.zeros_like(cls)
+ instances = []
  for shape in shapes:
  points = shape['points']
  label = shape['label']
+ group_id = shape.get('group_id')
+ if group_id is None:
+ group_id = uuid.uuid1()
  shape_type = shape.get('shape_type', None)
- if type == 'class':
-  cls_name = label
- elif type == 'instance':
- cls_name = label.split('-')[0]
-  if label not in instance_names:
-  instance_names.append(label)
-  ins_id = instance_names.index(label)
+
+ cls_name = label
+ instance = (cls_name, group_id)
+
+ if instance not in instances:
+ instances.append(instance)
+ ins_id = instances.index(instance) + 1
  cls_id = label_name_to_value[cls_name]
+
  mask = shape_to_mask(img_shape[:2], points, shape_type)
  cls[mask] = cls_id
- if type == 'instance':
- ins[mask] = ins_id
+ ins[mask] = ins_id
 
- if type == 'instance':
- return cls, ins
- return cls
+ return cls, ins
 
 
 def labelme_shapes_to_label(img_shape, shapes):
@@ -88,7 +87,7 @@ def labelme_shapes_to_label(img_shape, shapes):
  label_value = len(label_name_to_value)
  label_name_to_value[label_name] = label_value
 
- lbl = shapes_to_label(img_shape, shapes, label_name_to_value)
+ lbl, _ = shapes_to_label(img_shape, shapes, label_name_to_value)
  return lbl, label_name_to_value
 
 

tests/labelme_tests/utils_tests/test_shape.py

@@ -10,7 +10,7 @@ def test_shapes_to_label():
  label_name = shape['label']
  label_value = len(label_name_to_value)
  label_name_to_value[label_name] = label_value
- cls = shape_module.shapes_to_label(
+ cls, _ = shape_module.shapes_to_label(
  img.shape, data['shapes'], label_name_to_value)
  assert cls.shape == img.shape[:2]
 

tests/labelme_tests/utils_tests/util.py

@@ -31,7 +31,7 @@ def get_img_and_lbl():
  for label_name, label_value in label_name_to_value.items():
  label_names[label_value] = label_name
 
- lbl = shape_module.shapes_to_label(
+ lbl, _ = shape_module.shapes_to_label(
  img.shape, data['shapes'], label_name_to_value
  )
  return img, lbl, label_names