Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import torch
 import cv2
 import numpy as np
-from PIL import Image
+from PIL import Image, ImageEnhance
 from ultralytics import YOLO
 import json
 
@@ -11,20 +11,17 @@ model_path = "best.pt"
 model = YOLO(model_path)
 
 def preprocess_image(image):
-    """Apply enhancement filters and resize image before detection."""
-    image = np.array(image)
+    image = Image.fromarray(np.array(image))
 
-    
-    image = cv2.convertScaleAbs(image, alpha=0.8, beta=0)  # Brightness reduction
-    image = cv2.GaussianBlur(image, (3, 3), 0)  # Denoising
-    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])  # Sharpening
-    image = cv2.filter2D(image, -1, kernel)
+    image = ImageEnhance.Sharpness(image).enhance(2.0)  # Increase sharpness
+    image = ImageEnhance.Contrast(image).enhance(1.5)   # Increase contrast
+    image = ImageEnhance.Brightness(image).enhance(0.8) # Reduce brightness
 
-    
-    height, width = image.shape[:2]
-    new_width = 800
-    new_height = int((new_width / width) * height)
-    image = cv2.resize(image, (new_width, new_height))
+    # Resize image to 800px width while maintaining aspect ratio
+    width = 800
+    aspect_ratio = image.height / image.width
+    height = int(width * aspect_ratio)
+    image = image.resize((width, height))
 
     return image