Update app.py

app.py

@@ -324,25 +324,6 @@ def compress_image(
 
     return output.getvalue()
 
-# --------------------- Gradio ---------------------
-# with gr.Blocks() as demo:
-#     gr.Markdown("Face Swap")
-
-#     with gr.Row():
-#         src_input = gr.Image(type="numpy", label="Upload Your Face")
-#         tgt_input = gr.Image(type="numpy", label="Upload Target Image")
-
-#     btn = gr.Button("Swap Face")
-#     output_img = gr.Image(type="numpy", label="Enhanced Output")
-#     download = gr.File(label="⬇️ Download Enhanced Image")
-#     error_box = gr.Textbox(label="Logs / Errors", interactive=False)
-
-#     def process(src, tgt):
-#         img, path, err = face_swap_and_enhance(src, tgt)
-#         return img, path, err
-
-#     btn.click(process, [src_input, tgt_input], [output_img, download, error_box])
-
 # --------------------- DigitalOcean Spaces Helper ---------------------
 def get_spaces_client():
     session = boto3.session.Session()
@@ -389,6 +370,17 @@ def build_multi_faceswap_gradio():
         btn.click(process, [src, tgt], [out, error])
 
     return demo
+    
+def mandatory_enhancement(rgb_img):
+    """
+    Always runs CodeFormer on the final image.
+    Fail-safe: returns original if enhancement fails.
+    """
+    try:
+        return enhance_image_with_codeformer(rgb_img)
+    except Exception as e:
+        logger.error(f"CodeFormer failed, returning original: {e}")
+        return rgb_img
 
 # --------------------- API Endpoints ---------------------
 @fastapi_app.get("/")
@@ -787,912 +779,78 @@ async def preview_result(result_key: str):
         media_type="image/png",
         headers={"Content-Disposition": "inline; filename=result.png"}
     )
-# --------------------- Mount Gradio ---------------------
-
-multi_faceswap_app = build_multi_faceswap_gradio()
-fastapi_app = mount_gradio_app(
-    fastapi_app,
-    multi_faceswap_app,
-    path="/gradio-multi"
-)
-
-if __name__ == "__main__":
-    uvicorn.run(fastapi_app, host="0.0.0.0", port=7860)
-
-# # --------------------- List Images Endpoint ---------------------
-# import os
-# os.environ["OMP_NUM_THREADS"] = "1"
-# import shutil
-# import uuid
-# import cv2
-# import numpy as np
-# import threading
-# import subprocess
-# import logging
-# import tempfile
-# import sys
-# from datetime import datetime,timedelta
-
-# import insightface
-# from insightface.app import FaceAnalysis
-# from huggingface_hub import hf_hub_download
-# from fastapi import FastAPI, UploadFile, File, HTTPException, Response, Depends, Security, Form
-# from fastapi.responses import RedirectResponse
-# from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
-# from motor.motor_asyncio import AsyncIOMotorClient
-# from bson import ObjectId
-# from bson.errors import InvalidId
-# import httpx
-# import uvicorn
-# import gradio as gr
-# from gradio import mount_gradio_app
-# from PIL import Image
-# import io
-
-# # DigitalOcean Spaces
-# import boto3
-# from botocore.client import Config
-# from typing import Optional
-
-# # --------------------- Logging ---------------------
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # --------------------- Secrets & Paths ---------------------
-# REPO_ID = "HariLogicgo/face_swap_models"
-# MODELS_DIR = "./models"
-# os.makedirs(MODELS_DIR, exist_ok=True)
-
-# HF_TOKEN = os.getenv("HF_TOKEN")
-# API_SECRET_TOKEN = os.getenv("API_SECRET_TOKEN")
-
-# DO_SPACES_REGION = os.getenv("DO_SPACES_REGION", "blr1")
-# DO_SPACES_ENDPOINT = f"https://{DO_SPACES_REGION}.digitaloceanspaces.com"
-# DO_SPACES_KEY = os.getenv("DO_SPACES_KEY")
-# DO_SPACES_SECRET = os.getenv("DO_SPACES_SECRET")
-# DO_SPACES_BUCKET = os.getenv("DO_SPACES_BUCKET")
-
-# # NEW admin DB
-# ADMIN_MONGO_URL = os.getenv("ADMIN_MONGO_URL")
-# admin_client = AsyncIOMotorClient(ADMIN_MONGO_URL)
-# admin_db = admin_client.adminPanel
-# subcategories_col = admin_db.subcategories
-# media_clicks_col = admin_db.media_clicks
-
-# # OLD logs DB
-# MONGODB_URL = os.getenv("MONGODB_URL")
-# client = None
-# database = None
-
-# # --------------------- Download Models ---------------------
-# def download_models():
-#     logger.info("Downloading models...")
-#     inswapper_path = hf_hub_download(
-#         repo_id=REPO_ID,
-#         filename="models/inswapper_128.onnx",
-#         repo_type="model",
-#         local_dir=MODELS_DIR,
-#         token=HF_TOKEN
-#     )
-
-#     buffalo_files = ["1k3d68.onnx", "2d106det.onnx", "genderage.onnx", "det_10g.onnx", "w600k_r50.onnx"]
-#     for f in buffalo_files:
-#         hf_hub_download(
-#             repo_id=REPO_ID,
-#             filename=f"models/buffalo_l/" + f,
-#             repo_type="model",
-#             local_dir=MODELS_DIR,
-#             token=HF_TOKEN
-#         )
-
-#     logger.info("Models downloaded.")
-#     return inswapper_path
-
-
-# inswapper_path = download_models()
-
-# # --------------------- Face Analysis + Swapper ---------------------
-# providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
-# face_analysis_app = FaceAnalysis(name="buffalo_l", root=MODELS_DIR, providers=providers)
-# face_analysis_app.prepare(ctx_id=0, det_size=(640, 640))
-# swapper = insightface.model_zoo.get_model(inswapper_path, providers=providers)
-
-# # --------------------- CodeFormer ---------------------
-# CODEFORMER_PATH = "CodeFormer/inference_codeformer.py"
-
-# def ensure_codeformer():
-#     if not os.path.exists("CodeFormer"):
-#         subprocess.run("git clone https://github.com/sczhou/CodeFormer.git", shell=True, check=True)
-#         subprocess.run("pip install -r CodeFormer/requirements.txt", shell=True, check=True)
-#         subprocess.run("python CodeFormer/basicsr/setup.py develop", shell=True, check=True)
-#         subprocess.run("python CodeFormer/scripts/download_pretrained_models.py facelib", shell=True, check=True)
-#         subprocess.run("python CodeFormer/scripts/download_pretrained_models.py CodeFormer", shell=True, check=True)
-
-# ensure_codeformer()
-
-
-# # --------------------- FastAPI ---------------------
-# fastapi_app = FastAPI()
-
-# @fastapi_app.on_event("startup")
-# async def startup_db():
-#     global client, database
-#     logger.info("Initializing MongoDB for API logs...")
-#     client = AsyncIOMotorClient(MONGODB_URL)
-#     database = client.FaceSwap
-#     logger.info("MongoDB initialized for API logs")
-
-# @fastapi_app.on_event("shutdown")
-# async def shutdown_db():
-#     global client
-#     if client:
-#         client.close()
-#         logger.info("MongoDB connection closed")
-
-# # --------------------- Auth ---------------------
-# security = HTTPBearer()
-
-# def verify_token(credentials: HTTPAuthorizationCredentials = Security(security)):
-#     if credentials.credentials != API_SECRET_TOKEN:
-#         raise HTTPException(status_code=401, detail="Invalid or missing token")
-#     return credentials.credentials
-
-# # --------------------- Logging API Hits ---------------------
-# async def log_faceswap_hit(token: str, status: str = "success"):
-#     global database
-#     if database is None:
-#         return
-#     await database.api_logs.insert_one({
-#         "token": token,
-#         "endpoint": "/faceswap",
-#         "status": status,
-#         "timestamp": datetime.utcnow()
-#     })
-
-# # --------------------- Face Swap Pipeline ---------------------
-# swap_lock = threading.Lock()
-
-# def enhance_image_with_codeformer(rgb_img, temp_dir=None):
-#     if temp_dir is None:
-#         temp_dir = os.path.join(tempfile.gettempdir(), f"enhance_{uuid.uuid4().hex[:8]}")
-#     os.makedirs(temp_dir, exist_ok=True)
-
-#     input_path = os.path.join(temp_dir, "input.jpg")
-#     cv2.imwrite(input_path, cv2.cvtColor(rgb_img, cv2.COLOR_RGB2BGR))
-
-#     python_cmd = sys.executable if sys.executable else "python3"
-#     cmd = (
-#         f"{python_cmd} {CODEFORMER_PATH} "
-#         f"-w 0.4 "
-#         f"--input_path {input_path} "
-#         f"--output_path {temp_dir} "
-#         f"--bg_upsampler realesrgan "
-#         f"--face_upsample"
-#     )
-
-#     result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
-#     if result.returncode != 0:
-#         raise RuntimeError(result.stderr)
-
-#     final_dir = os.path.join(temp_dir, "final_results")
-#     files = [f for f in os.listdir(final_dir) if f.endswith(".png")]
-#     if not files:
-#         raise RuntimeError("No enhanced output")
-
-#     final_path = os.path.join(final_dir, files[0])
-#     enhanced = cv2.imread(final_path)
-#     return cv2.cvtColor(enhanced, cv2.COLOR_BGR2RGB)
-    
-# import numpy as np
-# from sklearn.metrics.pairwise import cosine_similarity
-
-# SIM_THRESHOLD = 0.35   # strict
-# MAX_YAW = 35
-# MAX_PITCH = 25
-# MIN_FACE_AREA = 10000
-
-
-# def face_ok(face):
-#     yaw, pitch, roll = face.pose
-#     x1, y1, x2, y2 = face.bbox
-#     area = (x2 - x1) * (y2 - y1)
-
-#     return (
-#         abs(yaw) <= MAX_YAW and
-#         abs(pitch) <= MAX_PITCH and
-#         area >= MIN_FACE_AREA
-#     )
-
-
-# def quality_score(face):
-#     yaw, pitch, roll = face.pose
-#     x1, y1, x2, y2 = face.bbox
-#     area = (x2 - x1) * (y2 - y1)
-#     return area - abs(yaw)*200 - abs(pitch)*150
-
-
-# def multi_face_swap_industry(src_img, tgt_img):
-#     """
-#     Industry-grade 2-face swap
-#     Returns swapped RGB image or raises error
-#     """
-
-#     src_bgr = cv2.cvtColor(src_img, cv2.COLOR_RGB2BGR)
-#     tgt_bgr = cv2.cvtColor(tgt_img, cv2.COLOR_RGB2BGR)
-
-#     src_faces = face_analysis_app.get(src_bgr)
-#     tgt_faces = face_analysis_app.get(tgt_bgr)
-
-#     if len(src_faces) < 1 or len(tgt_faces) < 1:
-#         raise ValueError("No faces detected")
-
-#     if len(src_faces) > 2 or len(tgt_faces) > 2:
-#         raise ValueError("More than 2 faces detected (blocked)")
-
-#     # ---- Quality filtering ----
-#     src_faces = [f for f in src_faces if face_ok(f)]
-#     tgt_faces = [f for f in tgt_faces if face_ok(f)]
-
-#     if not src_faces or not tgt_faces:
-#         raise ValueError("Faces rejected due to pose/quality")
-
-#     # ---- Sort by quality (best first) ----
-#     src_faces = sorted(src_faces, key=quality_score, reverse=True)
-#     tgt_faces = sorted(tgt_faces, key=quality_score, reverse=True)
-
-#     # ---- Extract embeddings ----
-#     src_embs = np.array([f.normed_embedding for f in src_faces])
-#     tgt_embs = np.array([f.normed_embedding for f in tgt_faces])
-
-#     sim = cosine_similarity(src_embs, tgt_embs)
-
-#     used_tgts = set()
-#     pairs = []
-
-#     for i in range(len(src_faces)):
-#         j = np.argmax(sim[i])
-#         score = sim[i][j]
-
-#         if score < SIM_THRESHOLD:
-#             raise ValueError(f"Low identity similarity ({score:.2f})")
-
-#         if j in used_tgts:
-#             continue
-
-#         pairs.append((src_faces[i], tgt_faces[j], score))
-#         used_tgts.add(j)
-
-#     if not pairs:
-#         raise ValueError("No valid face pairs")
-
-#     # ---- Swap WITHOUT re-detection ----
-#     result = tgt_bgr.copy()
-
-#     for src_face, tgt_face, score in pairs:
-#         result = swapper.get(
-#             result,
-#             tgt_face,
-#             src_face,
-#             paste_back=True
-#         )
-
-#     return cv2.cvtColor(result, cv2.COLOR_BGR2RGB)
     
-# # def multi_face_swap(src_img, tgt_img):
-# #     src_bgr = cv2.cvtColor(src_img, cv2.COLOR_RGB2BGR)
-# #     tgt_bgr = cv2.cvtColor(tgt_img, cv2.COLOR_RGB2BGR)
-
-# #     src_faces = face_analysis_app.get(src_bgr)
-# #     tgt_faces = face_analysis_app.get(tgt_bgr)
-
-# #     if not src_faces or not tgt_faces:
-# #         raise ValueError("No faces detected")
-
-# #     def face_sort_key(face):
-# #         x1, y1, x2, y2 = face.bbox
-# #         area = (x2 - x1) * (y2 - y1)
-# #         cx = (x1 + x2) / 2
-# #         return (-area, cx)
-
-# #     # Split by gender
-# #     src_male = [f for f in src_faces if f.gender == 1]
-# #     src_female = [f for f in src_faces if f.gender == 0]
-
-# #     tgt_male = [f for f in tgt_faces if f.gender == 1]
-# #     tgt_female = [f for f in tgt_faces if f.gender == 0]
-
-# #     # Sort inside gender groups
-# #     src_male = sorted(src_male, key=face_sort_key)
-# #     src_female = sorted(src_female, key=face_sort_key)
-
-# #     tgt_male = sorted(tgt_male, key=face_sort_key)
-# #     tgt_female = sorted(tgt_female, key=face_sort_key)
-
-# #     # Build final swap pairs
-# #     pairs = []
-
-# #     for s, t in zip(src_male, tgt_male):
-# #         pairs.append((s, t))
-
-# #     for s, t in zip(src_female, tgt_female):
-# #         pairs.append((s, t))
-
-# #     # Fallback if gender mismatch
-# #     if not pairs:
-# #         src_faces = sorted(src_faces, key=face_sort_key)
-# #         tgt_faces = sorted(tgt_faces, key=face_sort_key)
-# #         pairs = list(zip(src_faces, tgt_faces))
-
-# #     result_img = tgt_bgr.copy()
-
-# #     for src_face, _ in pairs:
-# #         # 🔁 re-detect current target faces
-# #         current_faces = face_analysis_app.get(result_img)
-# #         current_faces = sorted(current_faces, key=face_sort_key)
-
-# #         # choose best matching gender
-# #         candidates = [
-# #             f for f in current_faces if f.gender == src_face.gender
-# #         ] or current_faces
-
-# #         target_face = candidates[0]
-
-# #         result_img = swapper.get(
-# #             result_img,
-# #             target_face,
-# #             src_face,
-# #             paste_back=True
-# #         )
-
-# #     return cv2.cvtColor(result_img, cv2.COLOR_BGR2RGB)
-
-
-
-# def face_swap_and_enhance(src_img, tgt_img, temp_dir=None):
-#     try:
-#         with swap_lock:
-#             # Use a temp dir for intermediate files
-#             if temp_dir is None:
-#                 temp_dir = os.path.join(tempfile.gettempdir(), f"faceswap_work_{uuid.uuid4().hex[:8]}")
-#             if os.path.exists(temp_dir):
-#                 shutil.rmtree(temp_dir)
-#             os.makedirs(temp_dir, exist_ok=True)
-
-#             src_bgr = cv2.cvtColor(src_img, cv2.COLOR_RGB2BGR)
-#             tgt_bgr = cv2.cvtColor(tgt_img, cv2.COLOR_RGB2BGR)
-
-#             src_faces = face_analysis_app.get(src_bgr)
-#             tgt_faces = face_analysis_app.get(tgt_bgr)
-#             if not src_faces or not tgt_faces:
-#                 return None, None, "❌ Face not detected in one of the images"
-
-#             swapped_path = os.path.join(temp_dir, f"swapped_{uuid.uuid4().hex[:8]}.jpg")
-#             swapped_rgb = multi_face_swap_industry(src_img, tgt_img)
-#             swapped_bgr = cv2.cvtColor(swapped_rgb, cv2.COLOR_RGB2BGR)
-
-#             if swapped_bgr is None:
-#                 return None, None, "❌ Face swap failed"
-
-#             cv2.imwrite(swapped_path, swapped_bgr)
-
-#             python_cmd = sys.executable if sys.executable else "python3"
-#             cmd = f"{python_cmd} {CODEFORMER_PATH} -w 0.4 --input_path {swapped_path} --output_path {temp_dir} --bg_upsampler realesrgan --face_upsample"
-#             result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
-#             if result.returncode != 0:
-#                 return None, None, f"❌ CodeFormer failed:\n{result.stderr}"
-
-#             final_results_dir = os.path.join(temp_dir, "final_results")
-#             final_files = [f for f in os.listdir(final_results_dir) if f.endswith(".png")]
-#             if not final_files:
-#                 return None, None, "❌ No enhanced image found"
-
-#             final_path = os.path.join(final_results_dir, final_files[0])
-#             final_img_bgr = cv2.imread(final_path)
-#             if final_img_bgr is None:
-#                 return None, None, "❌ Failed to read enhanced image file"
-#             final_img = cv2.cvtColor(final_img_bgr, cv2.COLOR_BGR2RGB)
-
-#             return final_img, final_path, ""
-
-#     except Exception as e:
-#         return None, None, f"❌ Error: {str(e)}"
-        
-# def compress_image(
-#     image_bytes: bytes,
-#     max_size=(1280, 1280),   # max width/height
-#     quality=75               # JPEG quality (60–80 is ideal)
-# ) -> bytes:
-#     """
-#     Compress image by resizing and lowering quality.
-#     Returns compressed image bytes.
-#     """
-#     img = Image.open(io.BytesIO(image_bytes)).convert("RGB")
-
-#     # Resize while maintaining aspect ratio
-#     img.thumbnail(max_size, Image.LANCZOS)
-
-#     output = io.BytesIO()
-#     img.save(
-#         output,
-#         format="JPEG",
-#         quality=quality,
-#         optimize=True,
-#         progressive=True
-#     )
-
-#     return output.getvalue()
-
-# # --------------------- Gradio ---------------------
-# # with gr.Blocks() as demo:
-# #     gr.Markdown("Face Swap")
-
-# #     with gr.Row():
-# #         src_input = gr.Image(type="numpy", label="Upload Your Face")
-# #         tgt_input = gr.Image(type="numpy", label="Upload Target Image")
-
-# #     btn = gr.Button("Swap Face")
-# #     output_img = gr.Image(type="numpy", label="Enhanced Output")
-# #     download = gr.File(label="⬇️ Download Enhanced Image")
-# #     error_box = gr.Textbox(label="Logs / Errors", interactive=False)
-
-# #     def process(src, tgt):
-# #         img, path, err = face_swap_and_enhance(src, tgt)
-# #         return img, path, err
-
-# #     btn.click(process, [src_input, tgt_input], [output_img, download, error_box])
-
-# # --------------------- DigitalOcean Spaces Helper ---------------------
-# def get_spaces_client():
-#     session = boto3.session.Session()
-#     client = session.client(
-#         's3',
-#         region_name=DO_SPACES_REGION,
-#         endpoint_url=DO_SPACES_ENDPOINT,
-#         aws_access_key_id=DO_SPACES_KEY,
-#         aws_secret_access_key=DO_SPACES_SECRET,
-#         config=Config(signature_version='s3v4')
-#     )
-#     return client
-
-# def upload_to_spaces(file_bytes, key, content_type="image/png"):
-#     client = get_spaces_client()
-#     client.put_object(Bucket=DO_SPACES_BUCKET, Key=key, Body=file_bytes, ContentType=content_type, ACL='public-read')
-#     return f"{DO_SPACES_ENDPOINT}/{DO_SPACES_BUCKET}/{key}"
-
-# def download_from_spaces(key):
-#     client = get_spaces_client()
-#     obj = client.get_object(Bucket=DO_SPACES_BUCKET, Key=key)
-#     return obj['Body'].read()
-
-# def build_multi_faceswap_gradio():
-#     with gr.Blocks() as demo:
-#         gr.Markdown("## 👩‍❤️‍👨 Multi Face Swap (Couple → Couple)")
-
-#         with gr.Row():
-#             src = gr.Image(type="numpy", label="Source Image (2 Faces)")
-#             tgt = gr.Image(type="numpy", label="Target Image (2 Faces)")
-
-#         out = gr.Image(type="numpy", label="Swapped Result")
-#         error = gr.Textbox(label="Logs", interactive=False)
-
-#         def process(src_img, tgt_img):
-#             try:
-#                 swapped = multi_face_swap_industry(src_img, tgt_img)
-#                 enhanced = enhance_image_with_codeformer(swapped)
-#                 return enhanced, ""
-#             except Exception as e:
-#                 return None, str(e)
-
-#         btn = gr.Button("Swap Faces")
-#         btn.click(process, [src, tgt], [out, error])
-
-#     return demo
-
-# # --------------------- API Endpoints ---------------------
-# @fastapi_app.get("/")
-# def root():
-#     return {"status": "healthy"}
-
-# @fastapi_app.get("/health")
-# async def health():
-#     return {"status": "healthy"}
-
-# from fastapi import Form
-# import requests
-# @fastapi_app.get("/test-admin-db")
-# async def test_admin_db():
-#     try:
-#         doc = await admin_db.list_collection_names()
-#         return {"ok": True, "collections": doc}
-#     except Exception as e:
-#         return {"ok": False, "error": str(e), "url": ADMIN_MONGO_URL}
-
-# @fastapi_app.post("/face-swap", dependencies=[Depends(verify_token)])
-# async def face_swap_api(
-#     source: UploadFile = File(...),
-#     target_category_id: str = Form(None),
-#     new_category_id: str = Form(None),
-#     user_id: Optional[str] = Form(None),
-#     credentials: HTTPAuthorizationCredentials = Security(security)
-# ):
-#     start_time = datetime.utcnow()
-
-#     try:
-#         # ------------------------------------------------------------------
-#         # VALIDATION
-#         # ------------------------------------------------------------------
-#         # --------------------------------------------------------------
-#         # BACKWARD COMPATIBILITY FOR OLD ANDROID VERSIONS
-#         # --------------------------------------------------------------
-#         if target_category_id == "":
-#             target_category_id = None
-        
-#         if new_category_id == "":
-#             new_category_id = None
-        
-#         if user_id == "":
-#             user_id = None
-
-#         logger.info(f"[FaceSwap] Incoming request → target_category_id={target_category_id}, new_category_id={new_category_id}, user_id={user_id}")
-
-#         if target_category_id and new_category_id:
-#             raise HTTPException(400, "Provide only one of new_category_id or target_category_id.")
+@fastapi_app.post("/multi-face-swap", dependencies=[Depends(verify_token)])
+async def multi_face_swap_api(
+    source_image: UploadFile = File(...),
+    target_image: UploadFile = File(...)
+):
+    start_time = datetime.utcnow()
 
-#         if not target_category_id and not new_category_id:
-#             raise HTTPException(400, "Either new_category_id or target_category_id is required.")
+    try:
+        # -----------------------------
+        # Read images
+        # -----------------------------
+        src_bytes = await source_image.read()
+        tgt_bytes = await target_image.read()
 
-#         # ------------------------------------------------------------------
-#         # READ SOURCE IMAGE
-#         # ------------------------------------------------------------------
-#         src_bytes = await source.read()
-#         src_key = f"faceswap/source/{uuid.uuid4().hex}_{source.filename}"
-#         upload_to_spaces(src_bytes, src_key, content_type=source.content_type)
+        src_bgr = cv2.imdecode(np.frombuffer(src_bytes, np.uint8), cv2.IMREAD_COLOR)
+        tgt_bgr = cv2.imdecode(np.frombuffer(tgt_bytes, np.uint8), cv2.IMREAD_COLOR)
 
-#         # ------------------------------------------------------------------
-#         # CASE 1 : new_category_id → MongoDB lookup
-#         # ------------------------------------------------------------------
-#         if new_category_id:
+        if src_bgr is None or tgt_bgr is None:
+            raise HTTPException(400, "Invalid image data")
 
-#             doc = await subcategories_col.find_one({
-#                 "asset_images._id": ObjectId(new_category_id)
-#             })
+        src_rgb = cv2.cvtColor(src_bgr, cv2.COLOR_BGR2RGB)
+        tgt_rgb = cv2.cvtColor(tgt_bgr, cv2.COLOR_BGR2RGB)
 
-#             if not doc:
-#                 raise HTTPException(404, "Asset image not found in database")
+        # -----------------------------
+        # Multi-face swap
+        # -----------------------------
+        swapped_rgb = multi_face_swap(src_rgb, tgt_rgb)
 
-#             # extract correct asset
-#             asset = next(
-#                 (img for img in doc["asset_images"] if str(img["_id"]) == new_category_id),
-#                 None
-#             )
+        # -----------------------------
+        # 🔥 MANDATORY ENHANCEMENT
+        # -----------------------------
+        final_rgb = mandatory_enhancement(swapped_rgb)
 
-#             if not asset:
-#                 raise HTTPException(404, "Asset image URL not found")
+        final_bgr = cv2.cvtColor(final_rgb, cv2.COLOR_RGB2BGR)
 
-#             # correct URL
-#             target_url = asset["url"]
+        # -----------------------------
+        # Save temp result
+        # -----------------------------
+        temp_dir = tempfile.mkdtemp(prefix="multi_faceswap_")
+        result_path = os.path.join(temp_dir, "result.png")
+        cv2.imwrite(result_path, final_bgr)
 
-#             # correct categoryId (ObjectId)
-#             #category_oid = doc["categoryId"]   # <-- DO NOT CONVERT TO STRING
-#             subcategory_oid = doc["_id"]
-    
-#             # ------------------------------------------------------------------#
-#             # # MEDIA_CLICKS (ONLY IF user_id PRESENT)
-#             # ------------------------------------------------------------------#
-#             if user_id:
-#                 try:
-#                     user_id_clean = user_id.strip()
-#                     if not user_id_clean:
-#                         raise ValueError("user_id cannot be empty")
-#                     try:
-#                         user_oid = ObjectId(user_id_clean)
-#                     except (InvalidId, ValueError) as e:
-#                         logger.error(f"Invalid user_id format: {user_id_clean}")
-#                         raise ValueError(f"Invalid user_id format: {user_id_clean}")
-                    
-#                     now = datetime.utcnow()
-            
-#                     # Normalize dates (UTC midnight)
-#                     today_date = datetime(now.year, now.month, now.day)
-            
-#                     # -------------------------------------------------
-#                     # STEP 1: Ensure root document exists
-#                     # -------------------------------------------------
-#                     await media_clicks_col.update_one(
-#                         {"userId": user_oid},
-#                         {
-#                             "$setOnInsert": {
-#                                 "userId": user_oid,
-#                                 "createdAt": now,
-#                                 "ai_edit_complete": 0,
-#                                 "ai_edit_daily_count": []
-#                             }
-#                         },
-#                         upsert=True
-#                     )
-#                     # -------------------------------------------------
-#                     # STEP 2: Handle DAILY USAGE (BINARY, NO DUPLICATES)
-#                     # -------------------------------------------------
-#                     doc = await media_clicks_col.find_one(
-#                         {"userId": user_oid},
-#                         {"ai_edit_daily_count": 1}
-#                     )
-                    
-#                     daily_entries = doc.get("ai_edit_daily_count", []) if doc else []
-                    
-#                     # Normalize today to UTC midnight
-#                     today_date = datetime(now.year, now.month, now.day)
-                    
-#                     # Build normalized date → count map (THIS ENFORCES UNIQUENESS)
-#                     daily_map = {}
-#                     for entry in daily_entries:
-#                         d = entry["date"]
-#                         if isinstance(d, datetime):
-#                             d = datetime(d.year, d.month, d.day)
-#                         daily_map[d] = entry["count"]  # overwrite = no duplicates
-                    
-#                     # Determine last recorded date
-#                     last_date = max(daily_map.keys()) if daily_map else today_date
-                    
-#                     # Fill ALL missing days with count = 0
-#                     next_day = last_date + timedelta(days=1)
-#                     while next_day < today_date:
-#                         daily_map.setdefault(next_day, 0)
-#                         next_day += timedelta(days=1)
-                    
-#                     # Mark today as used (binary)
-#                     daily_map[today_date] = 1
-                    
-#                     # Rebuild list: OLDEST → NEWEST
-#                     final_daily_entries = [
-#                         {"date": d, "count": daily_map[d]}
-#                         for d in sorted(daily_map.keys())
-#                     ]
-                    
-#                     # Keep only last 32 days
-#                     final_daily_entries = final_daily_entries[-32:]
-                    
-#                     # Atomic replace
-#                     await media_clicks_col.update_one(
-#                         {"userId": user_oid},
-#                         {
-#                             "$set": {
-#                                 "ai_edit_daily_count": final_daily_entries,
-#                                 "updatedAt": now
-#                             }
-#                         }
-#                     )
-
-#                     # -------------------------------------------------
-#                     # STEP 3: Try updating existing subCategory
-#                     # -------------------------------------------------
-#                     update_result = await media_clicks_col.update_one(
-#                         {
-#                             "userId": user_oid,
-#                             "subCategories.subCategoryId": subcategory_oid
-#                         },
-#                         {
-#                             "$inc": {
-#                                 "subCategories.$.click_count": 1,
-#                                 "ai_edit_complete": 1
-#                             },
-#                             "$set": {
-#                                 "subCategories.$.lastClickedAt": now,
-#                                 "ai_edit_last_date": now,
-#                                 "updatedAt": now
-#                             }
-#                         }
-#                     )
-            
-#                     # -------------------------------------------------
-#                     # STEP 4: Push subCategory if missing
-#                     # -------------------------------------------------
-#                     if update_result.matched_count == 0:
-#                         await media_clicks_col.update_one(
-#                             {"userId": user_oid},
-#                             {
-#                                 "$inc": {
-#                                     "ai_edit_complete": 1
-#                                 },
-#                                 "$set": {
-#                                     "ai_edit_last_date": now,
-#                                     "updatedAt": now
-#                                 },
-#                                 "$push": {
-#                                     "subCategories": {
-#                                         "subCategoryId": subcategory_oid,
-#                                         "click_count": 1,
-#                                         "lastClickedAt": now
-#                                     }
-#                                 }
-#                             }
-#                         )
-                    
-#                     # -------------------------------------------------
-#                     # STEP 5: Sort subCategories by lastClickedAt (ascending - oldest first)
-#                     # -------------------------------------------------
-#                     user_doc = await media_clicks_col.find_one({"userId": user_oid})
-#                     if user_doc and "subCategories" in user_doc:
-#                         subcategories = user_doc["subCategories"]
-#                         # Sort by lastClickedAt in ascending order (oldest first)
-#                         # Handle missing or None dates by using datetime.min
-#                         subcategories_sorted = sorted(
-#                             subcategories,
-#                             key=lambda x: x.get("lastClickedAt") if x.get("lastClickedAt") is not None else datetime.min
-#                         )
-#                         # Update with sorted array
-#                         await media_clicks_col.update_one(
-#                             {"userId": user_oid},
-#                             {
-#                                 "$set": {
-#                                     "subCategories": subcategories_sorted,
-#                                     "updatedAt": now
-#                                 }
-#                             }
-#                         )
-            
-#                     logger.info(
-#                         "[MEDIA_CLICK] user=%s subCategory=%s ai_edit_complete++ daily_tracked",
-#                         user_id,
-#                         str(subcategory_oid)
-#                     )
-            
-#                 except Exception as media_err:
-#                     logger.error(f"MEDIA_CLICK ERROR: {media_err}")
-
-# #         # ------------------------------------------------------------------
-# #         # CASE 2 : target_category_id → DigitalOcean path (unchanged logic)
-# #         # ------------------------------------------------------------------
-#         if target_category_id:
-#             client = get_spaces_client()
-#             base_prefix = "faceswap/target/"
-#             resp = client.list_objects_v2(
-#                 Bucket=DO_SPACES_BUCKET, Prefix=base_prefix, Delimiter="/"
-#             )
-            
-#             # Extract categories from the CommonPrefixes
-#             categories = [p["Prefix"].split("/")[2] for p in resp.get("CommonPrefixes", [])]
+        with open(result_path, "rb") as f:
+            result_bytes = f.read()
 
-#             target_url = None
-            
-#             # --- FIX STARTS HERE ---
-#             for category in categories:
-#                 original_prefix = f"faceswap/target/{category}/original/"
-#                 thumb_prefix = f"faceswap/target/{category}/thumb/" # Keep for file list check (optional but safe)
-                
-#                 # List objects in original/
-#                 original_objects = client.list_objects_v2(
-#                     Bucket=DO_SPACES_BUCKET, Prefix=original_prefix
-#                 ).get("Contents", [])
-
-#                 # List objects in thumb/ (optional: for the old code's extra check)
-#                 thumb_objects = client.list_objects_v2(
-#                     Bucket=DO_SPACES_BUCKET, Prefix=thumb_prefix
-#                 ).get("Contents", [])
-                
-#                 # Extract only the filenames and filter for .png
-#                 original_filenames = sorted([
-#                     obj["Key"].split("/")[-1] for obj in original_objects 
-#                     if obj["Key"].split("/")[-1].endswith(".png")
-#                 ])
-#                 thumb_filenames = [
-#                     obj["Key"].split("/")[-1] for obj in thumb_objects
-#                 ]
-
-#                 # Replicate the old indexing logic based on sorted filenames
-#                 for idx, filename in enumerate(original_filenames, start=1):
-#                     cid = f"{category.lower()}image_{idx}"
-
-#                     # Optional: Replicate the thumb file check for 100% parity
-#                     # if filename in thumb_filenames and cid == target_category_id:
-#                     # Simpler check just on the ID, assuming thumb files are present
-#                     if cid == target_category_id:
-#                         # Construct the final target URL using the full prefix and the filename
-#                         target_url = f"{DO_SPACES_ENDPOINT}/{DO_SPACES_BUCKET}/{original_prefix}{filename}"
-#                         break
-                
-#                 if target_url:
-#                     break
-#             # --- FIX ENDS HERE ---
+        # -----------------------------
+        # Upload
+        # -----------------------------
+        result_key = f"faceswap/multi/{uuid.uuid4().hex}.png"
+        result_url = upload_to_spaces(
+            result_bytes,
+            result_key,
+            content_type="image/png"
+        )
 
-#             if not target_url:
-#                 raise HTTPException(404, "Target categoryId not found")
-# #         # ------------------------------------------------------------------
-# #         # DOWNLOAD TARGET IMAGE
-# #         # ------------------------------------------------------------------
-#         async with httpx.AsyncClient(timeout=30.0) as client:
-#             response = await client.get(target_url)
-#             response.raise_for_status()
-#             tgt_bytes = response.content
+        return {
+            "result_key": result_key,
+            "result_url": result_url
+        }
 
-#         src_bgr = cv2.imdecode(np.frombuffer(src_bytes, np.uint8), cv2.IMREAD_COLOR)
-#         tgt_bgr = cv2.imdecode(np.frombuffer(tgt_bytes, np.uint8), cv2.IMREAD_COLOR)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
 
-#         if src_bgr is None or tgt_bgr is None:
-#             raise HTTPException(400, "Invalid image data")
+# --------------------- Mount Gradio ---------------------
 
-#         src_rgb = cv2.cvtColor(src_bgr, cv2.COLOR_BGR2RGB)
-#         tgt_rgb = cv2.cvtColor(tgt_bgr, cv2.COLOR_BGR2RGB)
+multi_faceswap_app = build_multi_faceswap_gradio()
+fastapi_app = mount_gradio_app(
+    fastapi_app,
+    multi_faceswap_app,
+    path="/gradio-multi"
+)
 
-#         # ------------------------------------------------------------------
-#         # FACE SWAP EXECUTION
-#         # ------------------------------------------------------------------
-#         final_img, final_path, err = face_swap_and_enhance(src_rgb, tgt_rgb)
-#         if err:
-#             raise HTTPException(500, err)
-
-#         with open(final_path, "rb") as f:
-#             result_bytes = f.read()
-
-#         result_key = f"faceswap/result/{uuid.uuid4().hex}_enhanced.png"
-#         result_url = upload_to_spaces(result_bytes, result_key)
-#         # -------------------------------------------------
-#         # COMPRESS IMAGE (2–3 MB target)
-#         # -------------------------------------------------
-#         compressed_bytes = compress_image(
-#             image_bytes=result_bytes,
-#             max_size=(1280, 1280),
-#             quality=72
-#         )
-        
-#         compressed_key = f"faceswap/result/{uuid.uuid4().hex}_enhanced_compressed.jpg"
-#         compressed_url = upload_to_spaces(
-#             compressed_bytes,
-#             compressed_key,
-#             content_type="image/jpeg"
-#         )
-#         end_time = datetime.utcnow()
-#         response_time_ms = (end_time - start_time).total_seconds() * 1000
-
-#         if database is not None:
-#             await database.api_logs.insert_one({
-#                 "endpoint": "/face-swap",
-#                 "status": "success",
-#                 "response_time_ms": response_time_ms,
-#                 "timestamp": end_time
-#             })
-
-
-#         return {
-#             "result_key": result_key,
-#             "result_url": result_url,
-#             "Compressed_Image_URL": compressed_url
-#         }
-        
-#     except Exception as e:
-#         end_time = datetime.utcnow()
-#         response_time_ms = (end_time - start_time).total_seconds() * 1000
-
-#         if database is not None:
-#             await database.api_logs.insert_one({
-#                 "endpoint": "/face-swap",
-#                 "status": "fail",
-#                 "response_time_ms": response_time_ms,
-#                 "timestamp": end_time,
-#                 "error": str(e)
-#             })
-
-#         raise HTTPException(500, f"Face swap failed: {str(e)}")
-
-# @fastapi_app.get("/preview/{result_key:path}")
-# async def preview_result(result_key: str):
-#     try:
-#         img_bytes = download_from_spaces(result_key)
-#     except Exception:
-#         raise HTTPException(status_code=404, detail="Result not found")
-#     return Response(
-#         content=img_bytes,
-#         media_type="image/png",
-#         headers={"Content-Disposition": "inline; filename=result.png"}
-#     )
-# # --------------------- Mount Gradio ---------------------
-
-# multi_faceswap_app = build_multi_faceswap_gradio()
-# fastapi_app = mount_gradio_app(
-#     fastapi_app,
-#     multi_faceswap_app,
-#     path="/gradio-multi"
-# )
-
-# if __name__ == "__main__":
-#     uvicorn.run(fastapi_app, host="0.0.0.0", port=7860)
+if __name__ == "__main__":
+    uvicorn.run(fastapi_app, host="0.0.0.0", port=7860)