Revert change to dataloader that uses is_test flag.

src/code/custom_data_loading.py

@@ -14,15 +14,14 @@ class ImageImageDataLoaders(DataLoaders):
     """Basic wrapper around several `DataLoader`s with factory methods for Image to Image problems"""
     @classmethod
     @delegates(DataLoaders.from_dblock)
-    def from_label_func(cls, path, filenames, label_func, is_test, valid_pct=0.2, seed=None, item_transforms=None,
+    def from_label_func(cls, path, filenames, label_func, valid_pct=0.2, seed=None, item_transforms=None,
                         batch_transforms=None, **kwargs):
         """Create from list of `fnames` in `path`s with `label_func`."""
         datablock = DataBlock(blocks=(ImageBlock(cls=PILImage), ImageBlock(cls=PILImageBW)),
                               get_y=label_func,
+                              splitter=RandomSplitter(valid_pct, seed=seed),
                               item_tfms=item_transforms,
                               batch_tfms=batch_transforms)
-        if not is_test:
-            datablock.splitter = RandomSplitter(valid_pct, seed=seed)
         res = cls.from_dblock(datablock, filenames, path=path, **kwargs)
         return res
 
@@ -34,12 +33,11 @@ def get_y_fn(x):
     return y
 
 
-def create_data(data_path, is_test=False):
+def create_data(data_path):
     filenames = get_files(data_path, extensions='.jpg')
     if len(filenames) == 0:
         raise ValueError("Could not find any files in the given path")
     dataset = ImageImageDataLoaders.from_label_func(data_path,
-                                                    is_test=is_test,
                                                     seed=42,
                                                     bs=4, num_workers=0,
                                                     filenames=filenames,

src/code/eval.py

@@ -1,5 +1,5 @@
 import sys
-from fastai.vision.all import unet_learner, Path, resnet34, MSELossFlat
+from fastai.vision.all import unet_learner, Path, resnet34, MSELossFlat, get_files, L
 import torch
 from src.code.custom_data_loading import create_data
 from dagshub.fastai import DAGsHubLogger
@@ -39,8 +39,11 @@ if __name__ == "__main__":
         sys.exit(0)
 
     data_path = Path(sys.argv[1])
-    data = create_data(data_path, is_test=True)
+    data = create_data(data_path)
 
+    filenames = get_files(Path(sys.argv[1]), extensions='.jpg')
+    test_files = L([Path(i) for i in filenames])
+    test_dl = data.test_dl(test_files, with_labels=True)
     learner = unet_learner(data,
                            resnet34,
                            n_out=3,
@@ -48,5 +51,5 @@ if __name__ == "__main__":
                            path='src/',
                            model_dir='models')
     learner = learner.load('model')
-    predictions, targets = learner.get_preds()
+    predictions, targets = learner.get_preds(dl=test_dl)
     print(compute_errors(targets, predictions))