Update app.py

app.py

@@ -4,20 +4,16 @@ import numpy as np
 import requests
 from fastapi import FastAPI
 from pydantic import BaseModel
+from fastapi.responses import HTMLResponse
+from fastapi.middleware.cors import CORSMiddleware
 import insightface
 import gradio as gr
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.staticfiles import StaticFiles
 
-# -------------------------------------------
-# Load Face Model
-# -------------------------------------------
+# ---------- Load Face Detector ----------
 model = insightface.app.FaceAnalysis(name="buffalo_l")
 model.prepare(ctx_id=0, det_size=(640, 640))
 
-# -------------------------------------------
-# FastAPI app
-# -------------------------------------------
+# ---------- FastAPI App ----------
 app = FastAPI()
 
 # CORS for FlutterFlow
@@ -30,9 +26,7 @@ app.add_middleware(
 )
 
 
-# -------------------------------------------
-# Request Schema
-# -------------------------------------------
+# ---------- API Request Model ----------
 class CompareRequest(BaseModel):
     image1: str | None = None
     image2: str | None = None
@@ -40,9 +34,7 @@ class CompareRequest(BaseModel):
     image2_url: str | None = None
 
 
-# -------------------------------------------
-# Helper Functions
-# -------------------------------------------
+# ---------- Helpers ----------
 def b64_to_img(b64_string):
     try:
         img_data = base64.b64decode(b64_string)
@@ -52,7 +44,6 @@ def b64_to_img(b64_string):
     except:
         return None
 
-
 def url_to_img(url):
     try:
         resp = requests.get(url, timeout=5)
@@ -62,7 +53,6 @@ def url_to_img(url):
     except:
         return None
 
-
 def get_embedding(img):
     faces = model.get(img)
     if len(faces) == 0:
@@ -70,9 +60,7 @@ def get_embedding(img):
     return faces[0].embedding
 
 
-# -------------------------------------------
-# API Endpoint
-# -------------------------------------------
+# ---------- POST /compare ----------
 @app.post("/compare")
 async def compare_faces(req: CompareRequest):
 
@@ -93,35 +81,38 @@ async def compare_faces(req: CompareRequest):
         img2 = None
 
     if img1 is None or img2 is None:
-        return {"error": "Invalid image data or URL"}
+        return {"error": "Invalid image data or URL."}
 
     emb1 = get_embedding(img1)
     emb2 = get_embedding(img2)
 
     if emb1 is None or emb2 is None:
-        return {"error": "No face detected"}
+        return {"error": "No face detected."}
 
-    similarity = float(np.dot(emb1, emb2) / (np.linalg.norm(emb1) * np.linalg.norm(emb2)))
+    similarity = np.dot(emb1, emb2) / (
+        np.linalg.norm(emb1) * np.linalg.norm(emb2)
+    )
     matched = similarity > 0.55
 
-    return {"similarity": similarity, "match": matched}
+    return {
+        "similarity": float(similarity),
+        "match": matched
+    }
 
 
-# -------------------------------------------
-# Gradio UI (embedded inside FastAPI)
-# -------------------------------------------
+# ---------- Gradio UI ----------
 def gradio_ui(img1_text, img2_text):
-
-    def load_any(s):
+    # Detect format automatically
+    def load(s):
         if s.startswith("http"):
             return url_to_img(s)
         return b64_to_img(s)
 
-    img1 = load_any(img1_text)
-    img2 = load_any(img2_text)
+    img1 = load(img1_text)
+    img2 = load(img2_text)
 
     if img1 is None or img2 is None:
-        return "Invalid image or URL"
+        return "Invalid image."
 
     emb1 = get_embedding(img1)
     emb2 = get_embedding(img2)
@@ -129,20 +120,25 @@ def gradio_ui(img1_text, img2_text):
     if emb1 is None or emb2 is None:
         return "Face not detected."
 
-    similarity = float(np.dot(emb1, emb2) / (np.linalg.norm(emb1) * np.linalg.norm(emb2)))
-    matched = similarity > 0.55
+    similarity = np.dot(emb1, emb2) / (
+        np.linalg.norm(emb1) * np.linalg.norm(emb2)
+    )
+    match = similarity > 0.55
 
-    return f"Similarity: {similarity:.3f} | Match: {matched}"
+    return f"Similarity: {similarity:.3f} | Match: {match}"
 
 
-ui = gr.Interface(
+demo = gr.Interface(
     fn=gradio_ui,
     inputs=[
-        gr.Textbox(label="Image 1 (base64 or URL)"),
-        gr.Textbox(label="Image 2 (base64 or URL)"),
+        gr.Textbox(label="Image 1 (URL or Base64)"),
+        gr.Textbox(label="Image 2 (URL or Base64)")
     ],
     outputs="text",
-    title="Face Match API",
+    title="Face Compare API"
 )
 
-app = gr.mount_gradio_app(app, ui, path="/")
+# ---------- Serve Gradio UI at "/" ----------
+@app.get("/", response_class=HTMLResponse)
+async def root():
+    return demo.launch(share=False, inline=True)