Upload app.py with huggingface_hub

app.py

@@ -1,8 +1,8 @@
 """
-FaceAge-DINOv3 — Gradio demo for HuggingFace Spaces.
+FaceAge ClientScan — Gradio demo for HuggingFace Spaces.
 
 Face detection : YuNet (OpenCV built-in, ~350 KB model, no extra deps)
-Age/gender     : FaceAge-DINOv3 ONNX (CPU, ~1.2 GB)
+Age/gender     : FaceAge ClientScan ONNX (CPU, ~1.2 GB)
 """
 import os
 import numpy as np
@@ -60,7 +60,7 @@ def _load_age_model():
 
     print("[AgeModel] Downloading ONNX from HuggingFace Hub …")
     onnx_path = hf_hub_download(
-        repo_id  = "TrungTran/faceage-dino",
+        repo_id  = "TrungTran/faceage-clientscan",
         filename = "faceage_dino_fp32.onnx",
         token    = _HF_TOKEN,
     )
@@ -269,9 +269,9 @@ def predict(image: Image.Image, max_faces: int,
 # ---------------------------------------------------------------------------
 
 _DESC = """
-## FaceAge-DINOv3 — Age & Gender Estimation
+## FaceAge ClientScan — Age & Gender Estimation
 
-Upload a photo. **YuNet** auto-detects faces, then **FaceAge-DINOv3** predicts age and gender.
+Upload a photo. **YuNet** auto-detects faces, then **FaceAge ClientScan** predicts age and gender.
 
 | | |
 |--|--|
@@ -280,10 +280,10 @@ Upload a photo. **YuNet** auto-detects faces, then **FaceAge-DINOv3** predicts a
 | ⚡ Speed | ~100 ms / face on CPU (ONNX FP32) |
 | 🔍 Detector | YuNet (OpenCV, ~350 KB) |
 
-[📄 Model Card](https://huggingface.co/TrungTran/faceage-dino)
+[📄 Model Card](https://huggingface.co/TrungTran/faceage-clientscan)
 """
 
-with gr.Blocks(title="FaceAge-DINOv3", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="FaceAge ClientScan", theme=gr.themes.Soft()) as demo:
     gr.Markdown(_DESC)
 
     with gr.Row():