Update app.py

app.py

@@ -4,7 +4,7 @@ from cvlib.object_detection import draw_bbox
 import streamlit as st
 from PIL import Image
 from collections import Counter
-import os
+import cv2  # OpenCV for loading the YOLO model
 
 # Streamlit app title
 st.set_page_config(page_title="Object Detection App", page_icon="🖼️", layout="centered")
@@ -25,11 +25,12 @@ uploaded_file = st.file_uploader("Choose an image...", type=["png", "jpg", "jpeg
 def detect_common_objects_skip_progress(image, model='yolov3'):
     model_config = 'yolov3.cfg'  # Path to your downloaded .cfg file
     model_weights = 'yolov3.weights'  # Path to your downloaded .weights file
-    
-    # Perform object detection using the provided model files
-    box, label, count = cv.detect_common_objects(image, model=model, 
-                                                 model_config=model_config, 
-                                                 model_weights=model_weights)
+
+    # Load the YOLO model manually using OpenCV
+    net = cv2.dnn.readNet(model_weights, model_config)
+
+    # Perform object detection using cvlib (cvlib internally uses the loaded model)
+    box, label, count = cv.detect_common_objects(image, model='yolov3', net=net)
     return box, label, count
 
 if uploaded_file is not None:
@@ -38,24 +39,24 @@ if uploaded_file is not None:
 
     # Perform object detection with manually provided paths
     box, label, count = detect_common_objects_skip_progress(image)
-    
+
     # Draw bounding boxes on the image
     output_image = draw_bbox(image, box, label, count)
-    
+
     # Step 2: Display image with bounding boxes
     st.markdown("### Step 2: Detected Objects in the Image")
     st.image(output_image, channels="BGR", use_column_width=True)
-    
+
     # Step 3: Display the count of detected objects dynamically
     st.markdown("### Step 3: Detected Objects Count")
-    
+
     # Count each label in the image using Counter
     label_counts = Counter(label)
-    
+
     # Display counts in a well-formatted table
     for obj, count in label_counts.items():
         st.markdown(f"**{obj.capitalize()}s**: {count}")
-        
+
     st.markdown("""
     ---
     ### Tips: