Create app.py

app.py

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+import gradio as gr
+import torch
+from PIL import Image
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+# Load the Hugging Face model and processor for deepfake detection.
+processor = AutoImageProcessor.from_pretrained("Smogy/SMOGY-Ai-images-detector")
+model = AutoModelForImageClassification.from_pretrained("Smogy/SMOGY-Ai-images-detector")
+
+def detect_deepfake(image: Image.Image) -> str:
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    probs = torch.softmax(outputs.logits, dim=1)
+    idx = probs.argmax(dim=1).item()
+    label = model.config.id2label[idx]
+    conf = probs[0, idx].item()
+    return f"The image is {label} with confidence {conf:.2f}"
+
+# Build Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Deepfake Detection App")
+    gr.Markdown("### Upload an image to detect deepfake content.")
+    img_in = gr.Image(type="pil", label="Upload Image")
+    txt_out = gr.Textbox(label="Result")
+    gr.Button("Detect").click(fn=detect_deepfake, inputs=img_in, outputs=txt_out)
+
+if __name__ == "__main__":
+    demo.launch()