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import os
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import json
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import pandas as pd
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class ClinicDBSolver(object):
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CLSNAMES = [
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'colon',
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]
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def __init__(self, root='data/mvtec'):
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self.root = root
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self.meta_path = f'{root}/meta.json'
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def run(self):
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info = dict(train={}, test={})
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anomaly_samples = 0
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normal_samples = 0
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for cls_name in self.CLSNAMES:
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cls_dir = f'{self.root}'
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for phase in ['test']:
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cls_info = []
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img_names = os.listdir(f'{cls_dir}/images')
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mask_names = os.listdir(f'{cls_dir}/masks')
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img_names.sort()
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mask_names.sort() if mask_names is not None else None
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for idx, img_name in enumerate(img_names):
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info_img = dict(
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img_path=f'{cls_dir}/images/{img_name}',
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mask_path=f'{cls_dir}/masks/{mask_names[idx]}',
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cls_name=cls_name,
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specie_name='',
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anomaly=1
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)
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cls_info.append(info_img)
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if phase == 'test':
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if True:
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anomaly_samples = anomaly_samples + 1
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else:
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normal_samples = normal_samples + 1
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info[phase][cls_name] = cls_info
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with open(self.meta_path, 'w') as f:
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f.write(json.dumps(info, indent=4) + "\n")
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print('normal_samples', normal_samples, 'anomaly_samples', anomaly_samples)
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if __name__ == '__main__':
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runner = ClinicDBSolver(root='/remote-home/iot_zhouqihang/data/medical/CVC-ColonDB')
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runner.run()
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