initial commit

app.py

@@ -1,4 +1,12 @@
-import gradio as gr
+def classify(im):
+  features = feature_extractor(im, return_tensors='pt')
+  logits = model(features["pixel_values"])[-1]
+  probability = torch.nn.functional.softmax(logits, dim=-1)
+  probs = probability[0].detach().numpy()
+  confidences = {label: float(probs[i]) for i, label in enumerate(labels)} 
+  return confidences
+  
+ import gradio as gr
 
 sample_images=[['https://s3.amazonaws.com/moonup/production/uploads/1663933284359-611f9702593efbee33a4f7c9.png'],
 ['https://s3.amazonaws.com/moonup/production/uploads/1663933284374-611f9702593efbee33a4f7c9.png'],
@@ -6,7 +14,7 @@ sample_images=[['https://s3.amazonaws.com/moonup/production/uploads/166393328435
 
 title = 'Bean Leaf Classifier'
 description = 'This model is trained for beans leaf classification but might give a false result on other leaves'
-interface = gr.Interface(gr.Image(shape=(200, 200)), 'label',
+interface = gr.Interface(classify, gr.Image(shape=(200, 200)), 'label',
                          title = title,
                          description = description,
                          examples=sample_images)