Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import urllib.request
-import cv2
 import numpy as np
+import cv2
 from ultralytics import YOLO
 import gradio as gr
 
@@ -24,42 +24,31 @@ model = YOLO(MODEL_PATH)
 # --- Detection function ---
 def detect_objects(image):
     """
-    Input: image (BGR)
+    Input: image in BGR format (from Gradio/OpenCV)
     Output: annotated image, detected object names
     """
-    # Convert BGR (OpenCV) to RGB
+    # Convert BGR to RGB for YOLO
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
-    # Resize for consistent detection
-    image_resized = cv2.resize(image_rgb, (640, 640))
-
-    # Run YOLO inference with confidence threshold 0.2
-    results = model(image_resized, conf=0.2)
+    # Run YOLO inference directly on RGB image
+    results = model(image_rgb, conf=0.25)  # confidence threshold 25%
 
-    # Annotated image
+    # Annotated image (YOLO expects RGB, but plot returns RGB)
     annotated_image = results[0].plot()
 
-    # Extract detected class names
+    # Convert annotated image back to BGR for OpenCV/Gradio display
+    annotated_bgr = cv2.cvtColor(annotated_image, cv2.COLOR_RGB2BGR)
+
+    # Extract detected object names
     if results[0].boxes is not None:
         detected_classes = [model.names[int(c)] for c in results[0].boxes.cls]
         detected_text = ", ".join(detected_classes) if detected_classes else "No objects detected"
     else:
         detected_text = "No objects detected"
 
-    return annotated_image, detected_text
+    return annotated_bgr, detected_text
 
 # --- Gradio Interface ---
 demo = gr.Interface(
     fn=detect_objects,
-    inputs=gr.Image(type="numpy", label="Upload Image"),
-    outputs=[
-        gr.Image(type="numpy", label="Detected Objects"),
-        gr.Textbox(label="Objects Detected")
-    ],
-    title="🧠 Object Detection App",
-    description="Upload an image — YOLOv8s detects all objects and lists their names!"
-)
-
-# --- Launch the app ---
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    inputs=g