Raphaël Bournhonesque commited on
Commit
3dc0018
·
1 Parent(s): 4ebffee

improve app description

Browse files
Files changed (1) hide show
  1. app.py +11 -0
app.py CHANGED
@@ -7,6 +7,15 @@ import requests
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  import streamlit as st
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  http_session = requests.Session()
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  @enum.unique
@@ -69,6 +78,8 @@ barcode = st.sidebar.text_input(
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  "Product barcode", default_barcode
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  )
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  threshold = st.sidebar.number_input("Threshold", format="%f", value=0.5) or None
 
 
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  model_names = st.multiselect(
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  "Name of the model",
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  [x.name for x in NeuralCategoryClassifierModel],
 
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  import streamlit as st
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+ MODEL_DESCRIPTION = """
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+ **keras_2_0**: Current production model\n
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+ **keras_sota_3_0**: Best model (SOTA), trained on 300 epochs with product name, ingredients, OCR-extracted ingredients and nutriments as input\n
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+ **keras_ingredient_ocr_3_0**: same as `keras_sota_3_0`, but trained on less epochs\n
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+ **keras_baseline_3_0**: model trained with product name, ingredients and nutriments as input\n
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+ **keras_original_3_0**: same inputs as **keras_2_0** (product name + ingredients), but retrained\n
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+ **keras_product_name_only_3_0**: model with only product name as input
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+ """
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+
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  http_session = requests.Session()
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  @enum.unique
 
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  "Product barcode", default_barcode
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  )
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  threshold = st.sidebar.number_input("Threshold", format="%f", value=0.5) or None
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+
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+ st.sidebar.write("---\n# Model description\n" + MODEL_DESCRIPTION)
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  model_names = st.multiselect(
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  "Name of the model",
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  [x.name for x in NeuralCategoryClassifierModel],