Update app.py

app.py

@@ -1,8 +1,36 @@
+from transformers import ViTImageProcessor, ViTForImageClassification
+import torch
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+feature_extractor = ViTImageProcessor.from_pretrained("model_artifacts")
+model = ViTForImageClassification.from_pretrained("model_artifacts")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+labels = ['Chevrolet Equinox',
+ 'Chevrolet Silverado 1500',
+ 'Ford Escape',
+ 'Ford Explorer',
+ 'Ford F-150',
+ 'GMC Sierra 1500',
+ 'Honda CR-V',
+ 'Jeep Compass',
+ 'Jeep Grand Cherokee',
+ 'Jeep Wrangler',
+ 'Mazda CX-5',
+ 'Nissan Rogue',
+ 'RAM 1500',
+ 'RAM 2500',
+ 'Toyota Camry']
 
+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
+
+
+description = "Simple car recognition model"
+interface = gr.Interface(fn=classify, inputs="image", outputs="label", title="Car classification demo :)", description=description ) 
+
+interface.launch(debug=True)