Merge branch 'master' of https://github.com/BiaPyX/BiaPy

# Conflicts: # biapy/data/generators/pair_data_2D_generator.py Signed-off-by: Ignacio Arganda-Carreras <[email protected]>
BiaPyX · Feb 26, 2024 · 37f4bc5 · 37f4bc5
2 parents 11a3f52 + da89c67
commit 37f4bc5
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Showing 5 changed files with 6 additions and 4 deletions.
diff --git a/biapy/data/generators/pair_data_2D_generator.py b/biapy/data/generators/pair_data_2D_generator.py
@@ -30,7 +30,7 @@ def ensure_shape(self, img, mask):
 
         # Super-resolution check. if random_crops_in_DA is activated the images have not been cropped yet,
         # so this check can not be done and it will be done in the random crop
-        if not self.random_crops_in_DA and self.Y_provided and self.random_crop_scale != 1:
+        if not self.random_crops_in_DA and self.Y_provided and any([x != 1 for x in self.random_crop_scale]):
             s = [img.shape[0]*self.random_crop_scale[0], img.shape[1]*self.random_crop_scale[1]]
             if all(x!=y for x,y in zip(s,mask.shape[:-1])):
                 raise ValueError("Images loaded need to be LR and its HR version. LR shape:"

diff --git a/biapy/data/generators/pair_data_3D_generator.py b/biapy/data/generators/pair_data_3D_generator.py
@@ -49,7 +49,7 @@ def ensure_shape(self, img, mask):
 
         # Super-resolution check. if random_crops_in_DA is activated the images have not been cropped yet,
         # so this check can not be done and it will be done in the random crop
-        if not self.random_crops_in_DA and self.Y_provided and self.random_crop_scale != 1:
+        if not self.random_crops_in_DA and self.Y_provided and any([x != 1 for x in self.random_crop_scale]):
             s = [img.shape[0]*self.random_crop_scale[0], img.shape[1]*self.random_crop_scale[1], img.shape[2]*self.random_crop_scale[2]]
             if all(x!=y for x,y in zip(s,mask.shape[0:-1])):
                 raise ValueError("Images loaded need to be LR and its HR version. LR shape:"

diff --git a/biapy/engine/metrics.py b/biapy/engine/metrics.py
@@ -138,7 +138,7 @@ def __call__(self, y_pred, y_true):
                 y_true = (y_true/255).type(torch.long)
 
         if self.num_classes > 2:
-            return self.jaccard(y_pred, y_true.squeeze())
+            return self.jaccard(y_pred, y_true.squeeze() if y_true.shape[0] > 1 else y_true.squeeze().unsqueeze(0))
         else:
             return self.jaccard(y_pred, y_true)
 

diff --git a/biapy/engine/semantic_seg.py b/biapy/engine/semantic_seg.py
@@ -234,6 +234,8 @@ def after_merge_patches(self, pred):
             pred = (pred>0.5).astype(np.uint8)        
         if pred.ndim == 4 and self.cfg.PROBLEM.NDIM == '3D':
             pred = np.expand_dims(pred,0)
+        if pred.ndim == 3 and self.cfg.PROBLEM.NDIM == '2D':
+            pred = np.expand_dims(pred,0)
         save_tif(pred, self.cfg.PATHS.RESULT_DIR.PER_IMAGE_BIN, self.processing_filenames, verbose=self.cfg.TEST.VERBOSE)
 
     def after_merge_patches_by_chunks_proccess_patch(self, filename):

diff --git a/biapy/models/resunet.py b/biapy/models/resunet.py
@@ -66,7 +66,7 @@ class ResUNet(nn.Module):
     """
     def __init__(self, image_shape=(256, 256, 1), activation="ELU", feature_maps=[32, 64, 128, 256], drop_values=[0.1,0.1,0.1,0.1],
         batch_norm=False, k_size=3, upsample_layer="convtranspose", z_down=[2,2,2,2], n_classes=1, 
-        output_channels="BC", upsampling_factor=1, upsampling_position="pre"):
+        output_channels="BC", upsampling_factor=(), upsampling_position="pre"):
         super(ResUNet, self).__init__()
 
         self.depth = len(feature_maps)-1