Try this

app.py

@@ -1,8 +1,7 @@
-# Cell
-from fastai.vision.all import *
 import gradio as gr
+from fastai.vision.all import *
+import skimage
 
-# Cell
 learn = load_learner('model.pkl')
 
 labels = learn.dls.vocab
@@ -11,6 +10,10 @@ def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-demo = gr.Interface(predict, gr.Image(), "image")
-demo.launch()
-# gr.Interface(fn=predict, inputs=gr.Image(shape=(512, 512)), outputs=gr.Label(num_top_classes=3)).launch(share=True)
+title = "Adobe Building Classifier"
+description = "An Adobe Building classifier trained on pictures from duckduckgo with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+examples = []
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs="image",outputs=gr.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()

requirements.txt

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