Create app.py

app.py

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+import torch
+from transformers import ViTForImageClassification, ViTImageProcessor
+from PIL import Image
+import gradio as gr
+
+model = ViTForImageClassification.from_pretrained('vit-hateful-gesture-classification')
+processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224')
+
+class_names = ['cut_throat_gesture', 'finger_gun_to_the_head', 'middle_finger', 'slanted_eyes_gesture', 'swastika']
+
+def predict(image):
+    inputs = processor(images=image, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model(**inputs).logits
+    
+    predicted_class_idx = outputs.argmax(-1).item()
+    predicted_class = class_names[predicted_class_idx]
+    
+    return predicted_class
+
+iface = gr.Interface(fn=predict, 
+                     inputs=gr.inputs.Image(type="pil"), 
+                     outputs=gr.outputs.Label(num_top_classes=1),
+                     title="Hateful Gesture Detection",
+                     description="Upload an image to classify hateful gestures or symbols")
+
+if __name__ == "__main__":
+    iface.launch(share=True)