Create app2.py

app2.py

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+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import StreamingResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
+import torch
+import cv2
+import numpy as np
+import logging
+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('cartoon4')
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+
+@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 = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)  # Use IMREAD_UNCHANGED to keep the original format
+    
+    if frame is None:
+        logging.error("Failed to decode the image.")
+        return {"error": "Failed to decode the image. Please ensure the file is a valid image format."}
+
+    logging.info(f"Uploaded image shape: {frame.shape}")
+
+    # Process the uploaded image
+    aligned_face, instyle, message = model.detect_and_align_image(frame, top, bottom, left, right)
+    if aligned_face is None or instyle is None:
+        logging.error("Failed to process the image: No face detected or alignment failed.")
+        return {"error": message}
+
+    processed_image, message = model.image_toonify(aligned_face, instyle, model.exstyle, style_degree=0.5, style_type='cartoon1')
+    if processed_image is None:
+        logging.error("Failed to toonify the image.")
+        return {"error": message}
+
+    # Convert processed image to bytes
+    _, encoded_image = cv2.imencode('.jpg', processed_image)
+
+    # 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")