Update app.py

app.py

@@ -1,6 +1,11 @@
 import gradio as gr
 from fastai.vision.all import *
 
+# Re-define the GrayscaleTransform class (same as during training)
+class GrayscaleTransform(Transform):
+    def encodes(self, img: PILImage):
+        return img.convert("L")  # Convert to grayscale
+
 # Load the trained model
 learn = load_learner('export.pkl')
 
@@ -10,11 +15,7 @@ def classify_waterfowl(img):
     return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(probs))}
 
 # Create a Gradio interface
-interface = gr.Interface(
-    fn=classify_waterfowl,
-    inputs=gr.Image(type="pil"),  # User will upload an image for classification
-    outputs=gr.Label()  # Display the model's classification label
-)
+interface = gr.Interface(fn=classify_waterfowl, inputs=gr.Image(type="pil"), outputs=gr.Label())
 
 # Launch the Gradio app
-interface.launch()
+interface.launch()