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import gradio as gr
from PIL import Image
from vit_model_test import CustomModel
# Initialize the model
model = CustomModel()
def predict(image: Image.Image):
animation.visible = True # 讛专讗讛 讗转 讛讗谞讬诪爪讬讛
label, confidence = model.predict(image)
result = "AI image" if label == 1 else "Real image"
animation.visible = False # 讛住转专 讗转 讛讗谞讬诪爪讬讛
return result, f"Confidence: {confidence:.2f}%"
# Define the Gradio interface
demo = gr.Interface(
fn=predict,
inputs=gr.Image(type="pil"),
outputs=[gr.Textbox(), gr.Textbox()],
title="Vision Transformer Model",
description="Upload an image to classify it using the Vision Transformer model.",
live=True, # 诪讗驻砖专 讞讬讝讜讬 诪讬讬讚讬
)
# Add video component
animation = gr.Video("https://cdn-uploads.huggingface.co/production/uploads/66d6f1b3b50e35e1709bfdf7/x7Ud8PO9QPfmrTvBVcCKE.mp4", visible=False) # 讛讻谞讬住讬 讗转 讛-URL 讛谞讻讜谉
# Launch the Gradio interface
if __name__ == "__main__":
demo.launch()
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