Upload app (3).py

app (3).py

@@ -1,12 +1,36 @@
 import streamlit as st
+from PIL import Image
 from io import StringIO
 import pandas as pd
 from transformers import pipeline
 
+# Create an object detection pipeline
 classifier = pipeline("object-detection", model="chayanee/Detected_img")
+
 def main():
-    st.title("Detection Img")
-    st.button("click", type="primary")
+    st.title("Object Detection on Images")
+
+    # File Upload Widget
+    uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "png", "jpeg"])
+
+    if uploaded_file is not None:
+        # Display the uploaded image
+        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
+
+        # Perform object detection
+        image = Image.open(uploaded_file)
+        results = classifier(image)
+
+        # Display object detection results
+        st.subheader("Object Detection Results")
+        for result in results:
+            label = result["label"]
+            score = result["score"]
+            box = result["box"]
+            st.write(f"Label: {label}, Score: {score:.2f}")
+            st.image(image.crop(box), caption=f"Object: {label}", use_column_width=True)
+
+    st.button("Click to Detect Objects", type="primary")
 
 if __name__ == "__main__":
-    main()
+    main()