Update app.py

app.py

@@ -1,5 +1,23 @@
 import gradio as gr
+import datasets
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
 
+dataset = datasets.load_dataset('beans')
+
+extractor = AutoFeatureExtractor.from_pretrained("saved_model_files")
+model = AutoModelForImageClassification.from_pretrained("saved_model_files")
+
+labels = dataset['train'].features['labels'].names
+
+def classify(im):
+  features = feature_extractor(im, return_tensors='pt')
+  with torch.no_grad():
+    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
+  
 # Set gradio interface
 gr_interface = gr.Interface(classify, inputs='image', outputs='label', title='Bean Classification', description='Monitor your crops health in easier way')
 # Launch gradio