Update app.py

app.py

@@ -1,21 +1,26 @@
 import gradio as gr
 from fastai.vision.all import *
-from fastai.learner import load_learner
+import skimage
 
 learn = load_learner('model.pkl')
 
 labels = learn.dls.vocab
-def is_cat(x): return x[0].isupper() 
-
 def predict(img):
     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 Classifier"
-description = "A pet classifier trained on the duckduckgo search result 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>"
+description = "A test with happy and sad 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 = ['people-happy.jpeg','sad-man.jpg']
 
-gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=2),
-             title=title, description=description, article=article).launch()
+gr.Interface(
+    fn=predict,
+    inputs=gr.components.Image(),
+    outputs=gr.components.Label(num_top_classes=2),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+).launch()