Update main.py

main.py

@@ -2,10 +2,9 @@ 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
+import logging
 from io import BytesIO
 
 app = FastAPI()
@@ -19,8 +18,6 @@ def load_model():
     model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')
     model.load_model('cartoon4')
 
-import logging
-
 # Configure logging
 logging.basicConfig(level=logging.INFO)
 
@@ -35,11 +32,16 @@ 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)
-    logging.info(f"Uploaded image shape: {frame_rgb.shape}")
+    frame_bgr = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    
+    if frame_bgr 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_bgr.shape}")
 
     # Process the uploaded image
-    aligned_face, instyle, message = model.detect_and_align_image(frame_rgb, top, bottom, left, right)
+    aligned_face, instyle, message = model.detect_and_align_image(frame_bgr, 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}
@@ -49,7 +51,7 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
         logging.error("Failed to toonify the image.")
         return {"error": message}
 
-    # Convert BGR to RGB
+    # Convert BGR to RGB for display
     processed_image_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
 
     # Convert processed image to bytes
@@ -57,11 +59,12 @@ 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")
-
+    from fastapi.responses import FileResponse
+    return FileResponse(path="/app/AB/index.html", media_type="text/html")