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semantic_segmentation
Naoya Yamaguchi 65bbb127bd Update draw_label in labelme2voc.py %!s(int64=6) %!d(string=hai) anos
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.readme 4d4d26ef04 Update README.md %!s(int64=6) %!d(string=hai) anos
data_annotated 43c442db27 Add example of semantic_segmentation %!s(int64=7) %!d(string=hai) anos
data_dataset_voc c1a5a5ca78 Save pixel-wise labels as PNG file %!s(int64=6) %!d(string=hai) anos
README.md 4d4d26ef04 Update README.md %!s(int64=6) %!d(string=hai) anos
labelme2voc.py 65bbb127bd Update draw_label in labelme2voc.py %!s(int64=6) %!d(string=hai) anos
labels.txt 43c442db27 Add example of semantic_segmentation %!s(int64=7) %!d(string=hai) anos

README.md

Semantic Segmentation Example

Annotation

labelme data_annotated --labels labels.txt --nodata

Convert to VOC-like Dataset

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

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

Note that the reason why the label file is mostly black is it 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