Added support for non-RGB images

efficientnet_pytorch/model.py

@@ -190,10 +190,21 @@ def from_name(cls, model_name, override_params=None):
         blocks_args, global_params = get_model_params(model_name, override_params)
         return cls(blocks_args, global_params)
 
+    @classmethod
+    def from_pretrained(cls, model_name, num_classes=1000, in_channels = 3):
+        model = cls.from_name(model_name, override_params={'num_classes': num_classes})
+        load_pretrained_weights(model, model_name, load_fc=(num_classes == 1000))
+        if in_channels != 3:
+            Conv2d = get_same_padding_conv2d(image_size = model._global_params.image_size)
+            out_channels = round_filters(32, model._global_params)
+            model._conv_stem = Conv2d(in_channels, out_channels, kernel_size=3, stride=2, bias=False)
+        return model
+
     @classmethod
     def from_pretrained(cls, model_name, num_classes=1000):
         model = cls.from_name(model_name, override_params={'num_classes': num_classes})
         load_pretrained_weights(model, model_name, load_fc=(num_classes == 1000))
+
         return model
 
     @classmethod