Update main.py

main.py

@@ -1,4 +1,48 @@
-import os
+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()
 
-exec(os.environ.get('CODE'))
+# Load model and necessary components
+from vtoonify_model import Model
+model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')
+model.load_model('cartoon1-d')
+
+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(...)):
+    # 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-d')
+
+    # 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")