Update main.py

main.py

@@ -1,16 +1,10 @@
 from fastapi import FastAPI, File, UploadFile, Form
 from fastapi.responses import StreamingResponse
 from fastapi.staticfiles import StaticFiles
+
 import shutil
 import cv2
 import numpy as np
-import dlib
-from torchvision import transforms
-import torch.nn.functional as F
-import gradio as gr
-import os
-import torch
-import io
 from io import BytesIO
 
 app = FastAPI()
@@ -23,8 +17,7 @@ def load_model():
     from vtoonify_model import Model
     model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')
     model.load_model('cartoon1')
-    
-# Define endpoints
+
 @app.post("/upload/")
 async def process_image(file: UploadFile = File(...), top: int = Form(...), bottom: int = Form(...), left: int = Form(...), right: int = Form(...)):
     global model
@@ -42,11 +35,15 @@ async def process_image(file: UploadFile = File(...), top: int = Form(...), bott
     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)
+    _, encoded_image = cv2.imencode('.jpg', processed_image_rgb)
 
     # Return the processed image as a streaming response
-    return StreamingResponse(io.BytesIO(encoded_image.tobytes()), media_type="image/jpeg")
+    return StreamingResponse(BytesIO(encoded_image.tobytes()), media_type="image/jpeg")
+
 
 # Mount static files directory
 app.mount("/", StaticFiles(directory="AB", html=True), name="static")
@@ -55,3 +52,4 @@ app.mount("/", StaticFiles(directory="AB", html=True), name="static")
 @app.get("/")
 def index():
     return FileResponse(path="/app/AB/index.html", media_type="text/html")
+