Upload app.py

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 from ultralytics import YOLO
 import tempfile
-import pandas as pd
 
 
 model = YOLO('best.pt')
@@ -17,14 +16,13 @@ elif input_method == "Take a Picture":
     image_data = st.camera_input("Take a picture")
 
 if image_data is not None:
-    # Create a temporary file to store the input image
     with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as tmp_file:
         tmp_file.write(image_data.getvalue())
         image_path = tmp_file.name
 
     results = model(image_path)
 
-    category_names = results[0].names  
+    category_names = results[0].names 
 
     predictions = {}
     for cls_id, conf in zip(results[0].boxes.cls, results[0].boxes.conf):
@@ -36,14 +34,12 @@ if image_data is not None:
         else:
             predictions[class_name] = [conf]
 
-    num_masks = len(results[0].masks.masks) 
+    num_masks = len(results[0].masks.data)
 
     st.write(f"Total {num_masks} objects found.")
     for category, confidences in predictions.items():
         st.write(f"{len(confidences)} {category}: {['{:.2f}'.format(c) for c in confidences]}")
 
-    with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as output_tmp:
-        for result in results:
-            result.save(save_dir=output_tmp.name)
-        st.image(output_tmp.name, caption='Segmented Image', use_column_width=True)
-
+    for result in results:
+        plotted_img = result.plot()
+        st.image(plotted_img, caption='Segmented Image', use_column_width=True)