Update main.py

main.py

@@ -1,11 +1,9 @@
 from fastapi import FastAPI, File, UploadFile, Form
-from fastapi.responses import StreamingResponse
+from fastapi.responses import StreamingResponse, FileResponse
 from fastapi.staticfiles import StaticFiles
 import torch
-import shutil
 import cv2
 import numpy as np
-import io
 from io import BytesIO
 
 app = FastAPI()
@@ -20,7 +18,7 @@ def load_model():
     model.load_model('cartoon4')
 
 @app.post("/upload/")
-async def process_image(file: UploadFile = File(...), top: int = Form(...), bottom: int = Form(...), left: int = Form(...), right: int = Form(...)):
+async def process_image(file: UploadFile = File(...)):
     global model
     if model is None:
         load_model()
@@ -32,8 +30,13 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
     nparr = np.frombuffer(contents, np.uint8)
     frame_rgb = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
 
+    # Automatically detect and align the face
+    aligned_face, instyle, message = model.detect_and_align_image(frame_rgb, 0, 0, 0, 0)
+    
+    if instyle is None:
+        return {"error": "No face detected. Please try a different image."}
+
     # Process the uploaded image
-    aligned_face, instyle, message = model.detect_and_align_image(frame_rgb, top, bottom, left, right)
     processed_image, message = model.image_toonify(aligned_face, instyle, model.exstyle, style_degree=0.5, style_type='cartoon4')
 
     # Convert BGR to RGB
@@ -45,12 +48,10 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
     # Return the processed image as a streaming response
     return StreamingResponse(BytesIO(encoded_image.tobytes()), media_type="image/jpeg")
 
-
 # Mount static files directory
 app.mount("/", StaticFiles(directory="AB", html=True), name="static")
 
 # Define index route
 @app.get("/")
 def index():
-    return FileResponse(path="/app/AB/index.html", media_type="text/html")
-
+    return FileResponse(path="/app/AB/index.html", media_type="text/html")