Nuno-Tome commited on
Commit
88c1db0
1 Parent(s): d862984

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Browse files
Files changed (1) hide show
  1. app.py +9 -30
app.py CHANGED
@@ -15,24 +15,11 @@ DATASETS = [
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  MAX_N_LABELS = 5
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  SPLIT_TO_CLASSIFY = 'pasta'
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- # COL1, COL2 = st.columns([3, 1])
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- # CONTAINER_TOP = st.container()
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- # CONTAINER_BODY = st.container()
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- # CONTAINER_FULL = st.container()
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- # CONTAINER_LOOP = st.container()
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- COL1=""
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- COL2=""
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  COLS = st.columns([3, 1])
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- CONTAINER_TOP = st.container()
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- CONTAINER_BODY = st.container()
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- CONTAINER_FULL = st.container()
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- CONTAINER_LOOP = st.container()
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- #(image_object, classifier_pipeline)
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- #def classify_one_image(classifier_model, dataset_to_classify):
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- #classify_one_image(image_object, classifier_pipeline)
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  def classify_one_image(classifier_model, dataset_to_classify):
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@@ -103,17 +90,8 @@ def make_template():
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  def main():
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- make_template()
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-
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- # with CONTAINER_TOP:
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- # st.write("# Bulk Image Classification DEMO")
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-
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- COLS[0].write("# Bulk Image Classification DEMO")
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- # TODO Restart or reset your app
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- # if st.button("Restart"):
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- # # Code to restart or reset your app goes here
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- # import subprocess
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- # subprocess.call(["shutdown", "-r", "-t", "0"])
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  #with CONTAINER_BODY:
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  with COLS[0]:
@@ -121,14 +99,14 @@ def main():
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  st.write("Soon we will have a dataset template")
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  #Model
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- chosen_model_name = COLS[0].selectbox("Select the model to use", MODELS, index=0)
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  if chosen_model_name is not None:
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- COLS[0].write("You selected", chosen_model_name)
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  #Dataset
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- shosen_dataset_name = COLS[0].selectbox("Select the dataset to use", DATASETS, index=0)
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  if shosen_dataset_name is not None:
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- COLS[0].write("You selected", shosen_dataset_name)
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  #click to classify
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  #image_object = dataset['pasta'][0]
@@ -140,6 +118,7 @@ def main():
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  COLS[0].write(f"Classification result: {classification_result}")
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  #classification_array.append(classification_result)
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  #st.write("# FLAG 6")
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- #st.write(classification_array)
 
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  if __name__ == "__main__":
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  main()
 
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  MAX_N_LABELS = 5
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  SPLIT_TO_CLASSIFY = 'pasta'
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  COLS = st.columns([3, 1])
 
 
 
 
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+
 
 
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  def classify_one_image(classifier_model, dataset_to_classify):
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  def main():
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+
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+ COLS[0].write("# Bulk Image Classification App")
 
 
 
 
 
 
 
 
 
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  #with CONTAINER_BODY:
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  with COLS[0]:
 
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  st.write("Soon we will have a dataset template")
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  #Model
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+ chosen_model_name = COLS[0].selectbox(f"Select the model to use", MODELS, index=0)
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  if chosen_model_name is not None:
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+ COLS[0].write(f"You selected", chosen_model_name)
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  #Dataset
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+ shosen_dataset_name = COLS[0].selectbox(f"Select the dataset to use", DATASETS, index=0)
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  if shosen_dataset_name is not None:
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+ COLS[0].write(f"You selected", shosen_dataset_name)
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  #click to classify
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  #image_object = dataset['pasta'][0]
 
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  COLS[0].write(f"Classification result: {classification_result}")
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  #classification_array.append(classification_result)
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  #st.write("# FLAG 6")
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+ #st.write(classification_array)
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+
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  if __name__ == "__main__":
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  main()