Update main.py

main.py

@@ -1,57 +1,4 @@
-from fastapi import FastAPI, File, UploadFile, Form
-from fastapi.responses import StreamingResponse
-from fastapi.staticfiles import StaticFiles
-import torch
-import shutil
-import cv2
-import numpy as np
-import io
-from io import BytesIO
-
-app = FastAPI()
-
-# Load model and necessary components
-model = None
-
-def load_model():
-    global model
-    from vtoonify_model import Model
-    model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')
-    model.load_model('cartoon1')
-
-from fastapi.middleware.cors import CORSMiddleware
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],  # Adjust as needed, '*' allows requests from any origin
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-@app.post("/upload/")
-async def process_image(file: UploadFile = File(...), top: int = Form(...), bottom: int = Form(...), left: int = Form(...), right: int = Form(...)):
-    global model
-    if model is None:
-        load_model()
-
-    # Read the uploaded image file
-    contents = await file.read()
-
-    # Convert the uploaded image to numpy array
-    nparr = np.frombuffer(contents, np.uint8)
-    frame_rgb = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-
-    # 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='cartoon1')
-
-    # Convert BGR to RGB
-    processed_image_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
-
-    # Convert processed image to bytes
-    _, encoded_image = cv2.imencode('.jpg', processed_image_rgb)
-
-    # Return the processed image as a streaming response
-    return StreamingResponse(BytesIO(encoded_image.tobytes()), media_type="image/jpeg")
+import os
 
 
+exec(os.environ.get('CODE'))