Update app.py

app.py

@@ -8,6 +8,7 @@ from tensorflow.keras.applications.xception import preprocess_input as xcp_pre
 from tensorflow.keras.applications.efficientnet import preprocess_input as eff_pre
 from tensorflow.keras.preprocessing.image import img_to_array
 from huggingface_hub import hf_hub_download
+import gradio as gr
 
 # Load models
 xcp_path = hf_hub_download(repo_id="Zeyadd-Mostaffa/deepfake-image-detector_final", filename="xception_model.h5")
@@ -61,3 +62,14 @@ def predict_image(image_path):
             results.append({"face_id": f"face_{idx+1}", "label": label, "score": round(float(final_score), 3)})
 
     return results
+
+interface = gr.Interface(
+    fn=predict_image,  # your prediction function
+    inputs=gr.Image(type="filepath"),
+    outputs="json",
+    title="Deepfake Detector (Hybrid Strategy)",
+    description="If 1 face → predict full image. If >1 → predict each face."
+)
+
+# ✅ Required to start app
+interface.launch()