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app.py

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+import gradio as gr
+import numpy as np
+import cv2
+import insightface
+from insightface.app import FaceAnalysis
+
+# Global variable to store the InsightFace app instance
+# This is loaded once at the start for efficiency
+app = FaceAnalysis(providers=['CPUExecutionProvider'])
+app.prepare(ctx_id=0, det_size=(640, 640))
+
+def run_face_verification(selfie_image, id_card_image):
+    """
+    Compares a selfie image with an ID card image for face verification.
+    """
+    if selfie_image is None or id_card_image is None:
+        return "Please upload both a selfie and an ID card image.", None, None
+
+    # Step 1: Face Detection & Embedding for Selfie
+    faces_selfie = app.get(selfie_image)
+    if not faces_selfie:
+        return "No face detected in the selfie.", None, None
+    face_selfie = faces_selfie[0]
+    embedding_selfie = face_selfie.embedding
+
+    # Step 2: Face Detection & Embedding for ID Card Photo
+    faces_id = app.get(id_card_image)
+    if not faces_id:
+        return "No face detected in the ID card image.", None, None
+    face_id = faces_id[0]
+    embedding_id = face_id.embedding
+
+    # Step 3: Facial Matching
+    # The dot product of the embeddings gives a similarity score (cosine similarity)
+    similarity_score = np.dot(embedding_selfie, embedding_id)
+    
+    # Define a threshold for a positive match. This is a common value for InsightFace.
+    confidence_threshold = 0.35 
+
+    # Step 4: Verification Logic
+    result_text = f"Similarity Score: {similarity_score:.4f}\n"
+
+    if similarity_score >= confidence_threshold:
+        result_text += "Verdict: Faces match! ✅"
+    else:
+        result_text += "Verdict: Faces do NOT match! ❌"
+    
+    # Placeholder for future steps
+    result_text += "\n\nNote: Liveness and ID text verification are not yet implemented in this demo."
+
+    return result_text, similarity_score, similarity_score >= confidence_threshold
+
+# Define the Gradio interface
+# This creates the visual layout of your app.
+interface = gr.Interface(
+    fn=run_face_verification,
+    inputs=[
+        gr.Image(label="Selfie (Live Face)", type="pil"),
+        gr.Image(label="ID Card Photo", type="pil")
+    ],
+    outputs=[
+        gr.Textbox(label="Verification Result"),
+        gr.Number(label="Confidence Score"),
+        gr.Checkbox(label="Match Found")
+    ],
+    title="Open-Source Face and ID Verification",
+    description="Upload a selfie and an ID photo to check if they match. This is a basic demonstration of face matching using InsightFace. It does **not** include liveness detection or ID text verification.",
+    examples=[
+        ["examples/selfie.jpg", "examples/id_photo.jpg"],
+    ]
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

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+insightface==0.7.3
+onnxruntime==1.22.1
+opencv-python==4.12.0.88
+gradio==1.12.1