Fycking tired of errors

app.py

@@ -7,13 +7,12 @@ import streamlit as st
 from PIL import Image
 from huggingface_hub import hf_hub_download
 
-# Configure Streamlit UI
-st.title("Mosquito Detection from Camera Capture")
-st.write("Take a picture to detect mosquito breeding sites using SSD.")
-
 # Define dataset classes
 classes = ['dengue-regions', 'wet_surface']
+num_classes = len(classes) + 1  # Including background
 
+# Load Model
+st.title("Real-Time SSD Object Detection")
 if 'model' not in st.session_state:
     model_path = hf_hub_download(repo_id="DhominickJ/MosqScope", filename="mosquito_model.pth")
     model = ssd300_vgg16(pretrained=True)  # Multi-box Algorithm
@@ -21,6 +20,15 @@ if 'model' not in st.session_state:
     model.eval()
     st.session_state.model = model
 
+# Open webcam
+cap = cv2.VideoCapture(0)
+stframe = st.empty()
+
+transform = transforms.Compose([
+    transforms.Resize((300, 300)),
+    transforms.ToTensor()
+])
+
 captured_image = st.camera_input("Take a picture")
 if captured_image is not None:
     # Load image from Streamlit capture
@@ -31,7 +39,7 @@ if captured_image is not None:
     image_np = np.array(image)
 
     # Apply transformation for model input
-    image_tensor = transforms(image).unsqueeze(0)
+    image_tensor = transform(image).unsqueeze(0)
 
     # Run inference
     with torch.no_grad():
@@ -46,3 +54,5 @@ if captured_image is not None:
     # Display frame in Streamlit
     stframe.image(image_np, channels="RGB")
 
+cap.release()
+cv2.destroyAllWindows()