Update Space"

app.py

@@ -64,7 +64,7 @@ with col1:
     with st.expander('How to use it'):
         st.markdown(
         '''
-        1) Upload your P&ID or select example diagrams  📬
+        1) Select any example diagram  📬
         2) Set confidence threshold 📈
         3) Press to perform inference   🚀
         4) Visualize model predictions  🔎
@@ -75,14 +75,14 @@ st.write('##')
    
 col1, col2, col3 = st.columns(3, gap='large')
 with col1:
-    st.markdown('##### Input File')
+    #st.markdown('##### Input File')
     # set input image by upload
-    uploaded_file = st.file_uploader("Upload your diagram", type="pdf")
-    if uploaded_file:
-        temp_dir = tempfile.mkdtemp()
-        path = os.path.join(temp_dir, uploaded_file.name)
-        with open(path, "wb") as f:
-            f.write(uploaded_file.getvalue())
+    #uploaded_file = st.file_uploader("Upload your diagram", type="pdf")
+    #if uploaded_file:
+    #    temp_dir = tempfile.mkdtemp()
+    #    path = os.path.join(temp_dir, uploaded_file.name)
+    #    with open(path, "wb") as f:
+    #        f.write(uploaded_file.getvalue())
     # set input images from examples
     def radio_func(option):
         option_to_id = {
@@ -92,7 +92,7 @@ with col1:
         }
         return option_to_id[option]
     radio = st.radio(
-        'Or select from the following examples',
+        'Select from the following examples',
         options = ['factory_pid.png', 'plant_pid.png', 'processing_pid.png'],
         format_func = radio_func,
     )

utils.py

@@ -13,8 +13,8 @@ def sahi_yolov8m_inference(
     detection_model,
     slice_height=512,
     slice_width=512,
-    overlap_height_ratio=0.2,
-    overlap_width_ratio=0.2,
+    overlap_height_ratio=0.1,
+    overlap_width_ratio=0.1,
     image_size=640,
     postprocess_match_threshold=0.5,
 ):