Create app.py

app.py

@@ -0,0 +1,29 @@
+import datasets
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+import torch
+
+dataset = load_dataset('beans')
+
+extractor = AutoFeatureExtractor.from_pretrained("lucasdmpp/BeanLeaf")
+model = AutoModelForImageClassification.from_pretrained("lucasdmpp/BeanLeaf")
+
+labels = dataset['train'].features['labels'].names
+example_imgs = ["example_0.jpg", "example_1.jpg"]
+
+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
+
+interface = interface = gr.Interface(classify, inputs='image',
+                          outputs='label',
+                          title='Bean Classification', 
+                          description='Check the health of your bean leaves',
+                          examples = example_imgs)
+
+interface.launch(debug=True)