rucv
4 years ago
1 changed files with 0 additions and 58 deletions
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test.py
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| import torch | |||||
| from tqdm import tqdm | |||||
| from opt import opt | |||||
| from utils.metrics import evaluate | |||||
| import datasets | |||||
| from torch.utils.data import DataLoader | |||||
| from utils.comm import generate_model | |||||
| from utils.metrics import Metrics | |||||
| def test(): | |||||
| print('loading data......') | |||||
| test_data = getattr(datasets, opt.dataset)(opt.root, opt.test_data_dir, mode='test') | |||||
| test_dataloader = DataLoader(test_data, batch_size=1, shuffle=False, num_workers=opt.num_workers) | |||||
| total_batch = int(len(test_data) / 1) | |||||
| model = generate_model(opt) | |||||
| model.eval() | |||||
| # metrics_logger initialization | |||||
| metrics = Metrics(['recall', 'specificity', 'precision', 'F1', 'F2', | |||||
| 'ACC_overall', 'IoU_poly', 'IoU_bg', 'IoU_mean', 'Dice']) | |||||
| with torch.no_grad(): | |||||
| bar = tqdm(enumerate(test_dataloader), total=total_batch) | |||||
| for i, data in bar: | |||||
| img, gt = data['image'], data['label'] | |||||
| if opt.use_gpu: | |||||
| img = img.cuda() | |||||
| gt = gt.cuda() | |||||
| output = model(img) | |||||
| _recall, _specificity, _precision, _F1, _F2, \ | |||||
| _ACC_overall, _IoU_poly, _IoU_bg, _IoU_mean, _Dice = evaluate(output, gt) | |||||
| metrics.update(recall= _recall, specificity= _specificity, precision= _precision, | |||||
| F1= _F1, F2= _F2, ACC_overall= _ACC_overall, IoU_poly= _IoU_poly, | |||||
| IoU_bg= _IoU_bg, IoU_mean= _IoU_mean, Dice = _Dice | |||||
| ) | |||||
| metrics_result = metrics.mean(total_batch) | |||||
| print("Test Result:") | |||||
| print('recall: %.4f, specificity: %.4f, precision: %.4f, F1: %.4f, F2: %.4f, ' | |||||
| 'ACC_overall: %.4f, IoU_poly: %.4f, IoU_bg: %.4f, IoU_mean: %.4f' | |||||
| % (metrics_result['recall'], metrics_result['specificity'], metrics_result['precision'], | |||||
| metrics_result['F1'], metrics_result['F2'], metrics_result['ACC_overall'], | |||||
| metrics_result['IoU_poly'], metrics_result['IoU_bg'], metrics_result['IoU_mean'], metric_result['Dice'])) | |||||
| if __name__ == '__main__': | |||||
| if opt.mode == 'test': | |||||
| print('--- PolypSeg Test---') | |||||
| test() | |||||
| print('Done') |
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