forked from mrq/DL-Art-School
33 lines
1.4 KiB
Python
33 lines
1.4 KiB
Python
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import orjson
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from data.image_label_parser import VsNetImageLabeler
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# Translates from the label JSON output of the VS.NET UI to something more compact and usable.
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def convert_from_vsnet_labels():
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labeler = VsNetImageLabeler(['F:\\4k6k\datasets\\ns_images\\512_unsupervised\\categories.json',
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'F:\\4k6k\datasets\\ns_images\\512_unsupervised\\categories_new.json',
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'F:\\4k6k\datasets\\ns_images\\512_unsupervised\\categories_new_new.json'])
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# Proposed format:
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# 'config': { 'dim' }
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# 'labels': [{ 'label', 'key'}] <- ordered by label index.
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# 'images': {'file': [{ 'lid', 'top', 'left' }}
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# 'labelMap' {<mapping of string labels to ids>}
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out_dict = {
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'config': {
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'dim': next(iter(labeler.labeled_images.values()))[0]['patch_width']
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},
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'labels': [{'label': cat['label'], 'key': cat['keyBinding']} for cat in labeler.categories.values()],
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}
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out_dict['labelMap'] = {}
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for i, lbl in enumerate(out_dict['labels']):
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out_dict['labelMap'][lbl['label']] = i
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out_dict['images'] = {}
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for fname, ilbls in labeler.labeled_images.items():
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out_dict['images'][fname] = [{'lid': out_dict['labelMap'][il['label']], 'top': il['patch_top'], 'left': il['patch_left']} for il in ilbls]
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with open("label_editor.json", 'wb') as fout:
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fout.write(orjson.dumps(out_dict))
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if __name__ == '__main__':
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convert_from_vsnet_labels()
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