Upload app.py

app.py

@@ -1,20 +1,20 @@
 import gradio as gr
-     from fastai.vision.all import *
-     from huggingface_hub import from_pretrained_fastai
+from fastai.vision.all import *
+from huggingface_hub import from_pretrained_fastai
 
-     # Load your model from Hugging Face
-     learn = from_pretrained_fastai("Laiaromeu/totallyspies_classifier")
-     labels = learn.dls.vocab
+# Load your model from Hugging Face
+learn = from_pretrained_fastai("Laiaromeu/totallyspies_classifier")
+labels = learn.dls.vocab
 
-     # Prediction function
-     def predict(img):
-         img = PILImage.create(img)
-         pred, pred_idx, probs = learn.predict(img)
-         return {labels[i]: float(probs[i]) for i in range(len(labels))}
+# Prediction function
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-     # Create the Gradio interface
-     gr.Interface(
-         fn=predict, 
-         inputs=gr.Image(), 
-         outputs=gr.Label(num_top_classes=2)
-     ).launch()
+# Create the Gradio interface
+gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(), 
+    outputs=gr.Label(num_top_classes=2)
+).launch()