Update files

app.py

@@ -58,8 +58,8 @@ with col1:
     with st.expander('How to use it'):
         st.markdown(
         '''
-        1) Select any example diagram  👆🏻
-        2) Set confidence threshold 📈
+        1) Upload or select any example diagram  👆🏻
+        2) Set model parameters 📈
         3) Press to perform inference   🚀
         4) Visualize model predictions  🔎
         '''
@@ -69,7 +69,11 @@ st.write('##')
    
 col1, col2, col3 = st.columns(3, gap='large')
 with col1:
-    st.markdown('##### Input Data')
+    st.markdown('##### Set Input Image')
+    # set input image by upload
+    image_file = st.file_uploader(
+        'Upload your P&ID', type = ['jpg','jpeg','png']
+    )
     # set input images from examples
     def radio_func(option):
         option_to_id = {
@@ -84,12 +88,17 @@ with col1:
         format_func = radio_func,
     )
 with col2:
+    # visualize input image
+    if image_file is not None:
+        image = Image.open(image_file)
+    else:
+        image = sahi.utils.cv.read_image_as_pil(IMAGE_TO_URL[radio])
     st.markdown('##### Preview')
-    image = sahi.utils.cv.read_image_as_pil(IMAGE_TO_URL[radio])
     with st.container(border = True):
         st.image(image, use_column_width = True)
         
 with col3:
+    # set SAHI parameters
     st.markdown('##### Set model parameters')
     slice_size = st.slider(
         label = 'Slice Size', 

requirements.txt

@@ -1,5 +1,5 @@
 sahi==0.11.14
-streamlit-image-comparison==0.0.4
+streamlit-image-comparison
 streamlit
 ultralyticsplus
 

utils.py

@@ -9,12 +9,12 @@ TEMP_DIR = "temp"
 def sahi_yolov8m_inference(
     image,
     detection_model,
-    slice_height=1240,
-    slice_width=1240,
-    overlap_height_ratio=0.1,
-    overlap_width_ratio=0.1,
-    image_size=4960,
-    postprocess_match_threshold=0.8,
+    slice_height,
+    slice_width,
+    overlap_height_ratio,
+    overlap_width_ratio,
+    image_size,
+    postprocess_match_threshold,
 ):
     # sliced inference
     detection_model.image_size = image_size
@@ -31,7 +31,7 @@ def sahi_yolov8m_inference(
         image=numpy.array(image),
         object_prediction_list=prediction_result.object_prediction_list,
         rect_th=3,
-        text_size=3
+        text_size=2
     )
 
     output = Image.fromarray(visual_result["image"])