Update main.py

main.py

@@ -1,69 +1,4 @@
-from fastapi import FastAPI, UploadFile, File, Form, HTTPException
-from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
-from fastapi.staticfiles import StaticFiles
-from fastapi.templating import Jinja2Templates
-import insightface
-from insightface.app import FaceAnalysis
-from insightface.model_zoo import get_model
-import numpy as np
-import cv2
-import io
+import os
 
-app = FastAPI()
 
-# Initialize FaceAnalysis app and swapper
-face_analysis = FaceAnalysis(name='buffalo_l')
-face_analysis.prepare(ctx_id=0, det_size=(640, 640))
-swapper = get_model('inswapper_128.onnx', download=True, download_zip=True)
-
-@app.post("/swap_faces/")
-async def swap_faces(source_file: UploadFile = File(...),
-                     source_face_index: int = Form(...),
-                     destination_file: UploadFile = File(...),
-                     destination_face_index: int = Form(...)):
-    """Swaps faces between the source and destination images based on the specified face indices."""
-    source_bytes = await source_file.read()
-    destination_bytes = await destination_file.read()
-
-    # Decode images
-    source_image = cv2.imdecode(np.frombuffer(source_bytes, np.uint8), cv2.IMREAD_COLOR)
-    destination_image = cv2.imdecode(np.frombuffer(destination_bytes, np.uint8), cv2.IMREAD_COLOR)
-
-    # Face detection and sorting
-    faces_source = sort_faces(face_analysis.get(source_image))
-    if not faces_source:
-        raise HTTPException(status_code=400, detail="No faces detected in the source image.")
-    source_face = get_face(faces_source, source_face_index)
-
-    faces_destination = sort_faces(face_analysis.get(destination_image))
-    if not faces_destination:
-        raise HTTPException(status_code=400, detail="No faces detected in the destination image.")
-    destination_face = get_face(faces_destination, destination_face_index)
-
-    # Swap faces
-    result_image = swapper.get(destination_image, destination_face, source_face, paste_back=True)
-    
-    # Convert result_image back to bytes
-    _, result_bytes = cv2.imencode('.jpg', result_image)
-    
-    # Return the image bytes as a streaming response
-    return StreamingResponse(io.BytesIO(result_bytes), media_type="image/jpeg")
-
-def sort_faces(faces):
-    return sorted(faces, key=lambda x: x.bbox[0])
-
-def get_face(faces, face_id):
-    if len(faces) < face_id or face_id < 1:
-        raise ValueError(f"The image includes only {len(faces)} faces, however, you asked for face {face_id}")
-    return faces[face_id - 1]
-
-@app.exception_handler(ValueError)
-async def value_error_handler(request, exc):
-    """Custom exception handler to return JSON error responses for ValueError."""
-    return JSONResponse(status_code=400, content={"detail": str(exc)})
-
-app.mount("/", StaticFiles(directory="static", html=True), name="static")
-
-@app.get("/")
-def index() -> FileResponse:
-    return FileResponse(path="/app/static/index.html", media_type="text/html")
+exec(os.environ.get('API'))