Allow arbitrary channel dimensions in ImageDataGenerator

keras/preprocessing/image.py

@@ -636,8 +636,8 @@ class ImageDataGenerator(object):
         if x.ndim != 4:
             raise ValueError('Input to `.fit()` should have rank 4. '
                              'Got array with shape: ' + str(x.shape))
-        if x.shape[self.channel_axis] not in {1, 3, 4}:
-            raise ValueError(
+        if x.shape[self.channel_axis] not in {3, 4}:
+            warnings.warn(
                 'Expected input to be images (as Numpy array) '
                 'following the data format convention "' + self.data_format + '" '
                 '(channels on axis ' + str(self.channel_axis) + '), i.e. expected '

tests/keras/preprocessing/image_test.py

@@ -73,22 +73,11 @@ class TestImage:
         with pytest.raises(ValueError):
             x = np.random.random((3, 10, 10))
             generator.fit(x)
-        with pytest.raises(ValueError):
-            x = np.random.random((32, 3, 10, 10))
-            generator.fit(x)
-        with pytest.raises(ValueError):
-            x = np.random.random((32, 10, 10, 5))
-            generator.fit(x)
+
         # Test flow with invalid data
-        with pytest.raises(ValueError):
-            x = np.random.random((32, 10, 10, 5))
-            generator.flow(np.arange(x.shape[0]))
         with pytest.raises(ValueError):
             x = np.random.random((32, 10, 10))
             generator.flow(np.arange(x.shape[0]))
-        with pytest.raises(ValueError):
-            x = np.random.random((32, 3, 10, 10))
-            generator.flow(np.arange(x.shape[0]))
 
     def test_image_data_generator_fit(self):
         generator = image.ImageDataGenerator(