Update FastAPI_app.py

FastAPI_app.py

@@ -10,6 +10,7 @@ import asyncio
 
 import uvicorn
 import numpy as np
+import cv2 as cv
 from PIL import Image
 from fastapi import FastAPI, Form, UploadFile, File, Request, HTTPException
 from fastapi.responses import HTMLResponse
@@ -142,16 +143,16 @@ def generate_recipe_qwen(ingredient_names):
 # YOLOv8 model for ingredient detection
 def infer_image(pil_image):
     
-    # Convert PIL to RGB numpy array (YOLOv8 prefers this)
-    img_array = np.array(pil_image.convert('RGB'))  # Force RGB, no alpha
+    # Convert PIL → OpenCV format
+    open_cv_image = np.array(pil_image)
+    open_cv_image = open_cv_image[:, :, ::-1].copy()  # RGB → BGR
 
-    # Resize with PIL (safe and fast)
-    pil_resized = pil_image.convert('RGB').resize((640, 640), Image.Resampling.LANCZOS)
-    img_resized = np.array(pil_resized)
+    # Resize to 640x640, YOLOv8 default
+    img = cv.resize(open_cv_image, (640, 640))
 
     # Inference with low threshold
-    results = _yolo_model(img_resized, conf=0.2, iou=0.45, verbose=False)[0]
-    
+    results = _yolo_model(img, conf=0.2, iou=0.45, verbose=False)[0]
+
     detected = []
 
     if results.boxes is not None and len(results.boxes) > 0:
@@ -347,4 +348,4 @@ def health():
 
 # Run app
 if __name__ == "__main__":
-    uvicorn.run("FastAPI_app:app", host="0.0.0.0", port=7860)
+    uvicorn.run("FastAPI_app:app", host="0.0.0.0", port=7860, reload=True)