Delete test.py

test.py

@@ -1,58 +0,0 @@
-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')