Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from pathlib import Path
+
+# Load YOLOv5 model
+model = YOLO(weights='HandSignDetector.pt')  # Replace with the path to your best.pt model
+
+# Set up Streamlit
+st.title("YOLOv5 Object Detection with Streamlit")
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Read the uploaded image
+    image = Image.open(uploaded_file)
+
+    # Inference
+    results = model(image)
+
+    # Display the image with bounding boxes
+    st.image(image, channels="RGB", caption="Object Detection Result", use_column_width=True)
+
+    # Display probability and class for each box
+    for det in results.xyxy[0]:
+        label = int(det[5])
+        score = float(det[4])
+        box = det[:4].tolist()
+
+        # Draw box on the image
+        st.image(model.plot([image], boxes=[box], labels=[label], confidences=[score])[0],
+                 channels="RGB", caption=f"Class {label} - Confidence: {score:.2f}", use_column_width=True)