lets see

app.py

@@ -1,16 +1,22 @@
 import gradio as gr
 from fastai.vision.all import *
-
+import skimage
 learn = load_learner("model.pkl")
 
+labels = learn.dls.vocab
+
 def classify_garbage(img):
+    img = PILImage.create(img)
     pred,idx,probs  = learn.predict(img)
-    return(dict(zip(pred,map(float,probs))))
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 image = gr.inputs.Image(shape = (128,128))
-label = gr.outputs.Label()
+label = gr.outputs.Label(num_top_classes=7)
 title = "Garbage Classifier"
 description = "A Garbage classifier trained with fastai. Created as a demo for Gradio and HuggingFace Spaces."
 examples = ['paper24.jpg']
-iface = gr.Interface(fn=classify_garbage, inputs=image, outputs=label,examples=examples,title=title,description=description)
+interpretation='default'
+enable_queue=True
+
+iface = gr.Interface(fn=classify_garbage, inputs=image, outputs=label,examples=examples,title=title,description=description,interpretation=interpretation,enable_queue=enable_queue)
 iface.launch(inline=False)

requirements.txt

@@ -1 +1,2 @@
-fastai
+fastai
+scikit-image