let's deploy

app.py

@@ -1,7 +1,18 @@
 import gradio as gr
+from fastai.vision.all import *
+import skimage
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('model.pkl')
 
-    iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-    iface.launch()
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return pred
+
+title = "Bird Species Classifier"
+description = "A bird species classifier trained on Kaggle dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces(Only identifies bird species)."
+examples = ['3.jpg','5.jpg','images.jpeg']
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(224, 224)),outputs=gr.outputs.Label(num_top_classes=1),title=title,description=description,examples=examples,enable_queue=enable_queue).launch()