Update app.py

app.py

@@ -1,18 +1,17 @@
-import gradio as gr
-from deepface import DeepFace
-import numpy as np
 from PIL import Image
-import json
-import uuid
+from io import BytesIO
+import numpy as np
 import base64
+import uuid
 import pymongo
-from io import BytesIO
+import certifi
+from deepface import DeepFace
+import gradio as gr
+import json
 
 # =======================
 # MongoDB setup
 # =======================
-import certifi
-
 client = pymongo.MongoClient(
     "mongodb+srv://username:password@cluster0.n8pboqq.mongodb.net/?retryWrites=true&w=majority",
     tlsCAFile=certifi.where()
@@ -20,9 +19,8 @@ client = pymongo.MongoClient(
 db = client["faceDB"]
 face_collection = db["faceImg"]
 
-
 # =======================
-# Upload ảnh + lưu MongoDB
+# Upload ảnh + MongoDB
 # =======================
 def upload_image(image, name):
     try:
@@ -36,7 +34,6 @@ def upload_image(image, name):
         img_bytes = buffer.getvalue()
         img_base64 = base64.b64encode(img_bytes).decode('utf-8')
 
-        # Lưu vào MongoDB
         doc = {
             "_id": image_id,
             "name": name,
@@ -57,15 +54,20 @@ def recognize_face(image, image_id):
         if not doc:
             return "❌ Ảnh ID không tồn tại"
 
-        # Decode base64 từ MongoDB
+        # Decode base64 → lưu tạm
         img_bytes = base64.b64decode(doc['image'])
-        pil_image = Image.open(BytesIO(img_bytes))
-        img2 = np.array(pil_image)
+        temp_path = f"temp_{image_id}.png"
+        with open(temp_path, "wb") as f:
+            f.write(img_bytes)
 
+        # Lưu input ảnh tạm
         if isinstance(image, Image.Image):
             image = np.array(image)
+        pil_input = Image.fromarray(image)
+        input_path = f"input_{image_id}.png"
+        pil_input.save(input_path)
 
-        result = DeepFace.verify(img1_path=image, img2_path=img2)
+        result = DeepFace.verify(img1_path=input_path, img2_path=temp_path)
         output = {
             "Verified": result["verified"],
             "Khoảng cách": round(result["distance"], 4),
@@ -82,8 +84,12 @@ def analyze_face(image):
     try:
         if isinstance(image, Image.Image):
             image = np.array(image)
+        pil_image = Image.fromarray(image)
+        temp_path = f"analyze_{uuid.uuid4().hex}.png"
+        pil_image.save(temp_path)
+
         result = DeepFace.analyze(
-            img_path=image,
+            img_path=temp_path,
             actions=["age", "gender", "emotion", "race"],
             enforce_detection=False
         )