Update main.py

main.py

@@ -1,11 +1,10 @@
 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
+import logging
 from io import BytesIO
 
 app = FastAPI()
@@ -19,6 +18,9 @@ def load_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
@@ -30,27 +32,35 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
 
     # Convert the uploaded image to numpy array
     nparr = np.frombuffer(contents, np.uint8)
-    frame_rgb = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    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_rgb, top, bottom, left, right)
-    processed_image, message = model.image_toonify(aligned_face, instyle, model.exstyle, style_degree=0.5, style_type='cartoon1')
+    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}
 
-    # Convert BGR to RGB
-    processed_image_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
+    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_rgb)
+    _, 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")
-
+    return FileResponse(path="/app/AB/index.html", media_type="text/html")