Update app.py

app.py

@@ -1,20 +1,17 @@
 import gradio as gr
 from fastai.vision.all import *
-import skimage
 
 learn = load_learner('export.pkl')
-
 labels = learn.dls.vocab
+
 def predict(img):
+    img = img.resize((512, 512))  # Resize to 512x512
     img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
+    pred, pred_idx, probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
- 
-title = "Pet Breed Classifier"
-description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
-article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
-examples = ['siamese.jpg']
-interpretation='default'
-enable_queue=True
 
-gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", image_mode="RGB"),  # Updated component, compatible with PIL
+    outputs=gr.Label(num_top_classes=2)
+).launch(share=True)