Spaces:
Sleeping
Sleeping
add spinner for waiting
Browse files
app.py
CHANGED
@@ -311,7 +311,7 @@ def main():
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# Display the uploaded image if the user has uploaded an image
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if uploaded_file is not None:
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-
with st.spinner('
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original_image = get_image(uploaded_file)
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col1, col2 = st.columns(2)
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@@ -335,19 +335,20 @@ def main():
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with st.spinner('Processing...'):
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perform_inference(model_object, model_arrow, st.session_state.crop_image, score_threshold)
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st.session_state.prediction = modif_box_pos(st.session_state.prediction, object_dict)
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print('Detection completed!')
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# If the prediction has been made and the user has uploaded an image, display the options for the user to annotate the image
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if 'prediction' in st.session_state and uploaded_file is not None:
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#if st.session_state.prediction_up==True:
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# Force garbage collection after display
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gc.collect()
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# Display the uploaded image if the user has uploaded an image
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if uploaded_file is not None:
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with st.spinner('Waiting for image display...'):
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original_image = get_image(uploaded_file)
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col1, col2 = st.columns(2)
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with st.spinner('Processing...'):
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perform_inference(model_object, model_arrow, st.session_state.crop_image, score_threshold)
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st.session_state.prediction = modif_box_pos(st.session_state.prediction, object_dict)
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st.success('Detection completed!')
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print('Detection completed!')
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# If the prediction has been made and the user has uploaded an image, display the options for the user to annotate the image
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if 'prediction' in st.session_state and uploaded_file is not None:
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with st.spinner('Waiting for result display...'):
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display_options(st.session_state.crop_image, score_threshold)
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#if st.session_state.prediction_up==True:
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with st.spinner('Waiting for BPMN modeler...'):
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st.session_state.bpmn_xml = create_XML(st.session_state.prediction.copy(), st.session_state.text_mapping, st.session_state.scale)
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display_bpmn_xml(st.session_state.bpmn_xml)
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# Force garbage collection after display
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gc.collect()
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