Lingjie Zhu 9885f0703e use pycocotools API %!s(int64=6) %!d(string=hai) anos
..
.readme 01f10365f4 Update README.md %!s(int64=6) %!d(string=hai) anos
data_annotated 4f2e652483 Add examples/instance_segmentation %!s(int64=7) %!d(string=hai) anos
data_dataset_coco c1b1543e86 Fix labelme2coco.py to parse with pycocotools %!s(int64=6) %!d(string=hai) anos
data_dataset_voc 800dc25c43 Update examples/instance_segmentation/data_dataset_voc %!s(int64=6) %!d(string=hai) anos
README.md 6561c90029 -like -> -format %!s(int64=6) %!d(string=hai) anos
labelme2coco.py 9885f0703e use pycocotools API %!s(int64=6) %!d(string=hai) anos
labelme2voc.py f1526d7168 --labels required=True %!s(int64=6) %!d(string=hai) anos
labels.txt 4f2e652483 Add examples/instance_segmentation %!s(int64=7) %!d(string=hai) anos

README.md

Instance Segmentation Example

Annotation

labelme data_annotated --labels labels.txt --nodata

Convert to VOC-format Dataset

# It generates:
#   - data_dataset_voc/JPEGImages
#   - data_dataset_voc/SegmentationClass
#   - data_dataset_voc/SegmentationClassVisualization
#   - data_dataset_voc/SegmentationObject
#   - data_dataset_voc/SegmentationObjectVisualization
./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt


Fig 1. JPEG image (left), JPEG class label visualization (center), JPEG instance label visualization (right)

Note that the label file contains only very low label values (ex. 0, 4, 14), and 255 indicates the __ignore__ label value (-1 in the npy file).
You can see the label PNG file by following.

labelme_draw_label_png data_dataset_voc/SegmentationClassPNG/2011_000003.png   # left
labelme_draw_label_png data_dataset_voc/SegmentationObjectPNG/2011_000003.png  # right

Convert to COCO-format Dataset

# It generates:
#   - data_dataset_coco/JPEGImages
#   - data_dataset_coco/annotations.json
./labelme2coco.py data_annotated data_dataset_coco --labels labels.txt