🐛 Fix MapDe dist_filter Shape (#914)

- Fix `dist_filter` in `MapDe` model for multi-class output.

Explanation:
Previously, if we set `num_class` to more than 1, the model would still output 1 channel. This was because the `dist_filter` always had size of 1 in its first dimension, however the first dimension determines the number of output channels in the tensor produced by `torch.functional.F.conv2d`.
This PR changes this by repeating the filters the match the number of output classes.

tests/models/test_arch_mapde.py

@@ -48,3 +48,12 @@ def test_functionality(remote_sample: Callable) -> None:
     output = model.infer_batch(model, batch, device=select_device(on_gpu=ON_GPU))
     output = model.postproc(output[0])
     assert np.all(output[0:2] == [[19, 171], [53, 89]])
+
+
+def test_multiclass_output() -> None:
+    """Test the architecture for multi-class output."""
+    multiclass_model = MapDe(num_input_channels=3, num_classes=3)
+    test_input = torch.rand((1, 3, 252, 252))
+
+    output = multiclass_model(test_input)
+    assert output.shape == (1, 3, 252, 252)

tiatoolbox/models/architecture/mapde.py

@@ -199,8 +199,11 @@ def __init__(
             dtype=np.float32,
         )
 
-        dist_filter = np.expand_dims(dist_filter, axis=(0, 1))  # NCHW
+        # For conv2d, filter shape = (out_channels, in_channels//groups, H, W)
+        dist_filter = np.expand_dims(dist_filter, axis=(0, 1))
         dist_filter = np.repeat(dist_filter, repeats=num_classes * 2, axis=1)
+        # Need to repeat for out_channels
+        dist_filter = np.repeat(dist_filter, repeats=num_classes, axis=0)
 
         self.min_distance = min_distance
         self.threshold_abs = threshold_abs