Update caching (#1496)

train.py

@@ -412,7 +412,7 @@ if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--weights', type=str, default='yolov5s.pt', help='initial weights path')
     parser.add_argument('--cfg', type=str, default='', help='model.yaml path')
-    parser.add_argument('--data', type=str, default='data/coco128.yaml', help='data.yaml path')
+    parser.add_argument('--data', type=str, default='data/voc.yaml', help='data.yaml path')
     parser.add_argument('--hyp', type=str, default='data/hyp.scratch.yaml', help='hyperparameters path')
     parser.add_argument('--epochs', type=int, default=300)
     parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs')

utils/datasets.py

@@ -365,7 +365,7 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
         cache_path = Path(self.label_files[0]).parent.with_suffix('.cache')  # cached labels
         if cache_path.is_file():
             cache = torch.load(cache_path)  # load
-            if cache['hash'] != get_hash(self.label_files + self.img_files):  # dataset changed
+            if cache['hash'] != get_hash(self.label_files + self.img_files + [cache_path]):  # dataset changed
                 cache = self.cache_labels(cache_path)  # re-cache
         else:
             cache = self.cache_labels(cache_path)  # cache