Nuno-Tome commited on
Commit
d862984
1 Parent(s): aad65ce

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Files changed (1) hide show
  1. app.py +11 -11
app.py CHANGED
@@ -64,7 +64,7 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
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  #dataset
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  dataset = load_dataset(shosen_dataset_name,"testedata_readme")
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- with CONTAINER_LOOP:
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  #Image teste load
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  image_object = dataset['pasta'][0]["image"]
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  st.image(image_object, caption="Uploaded Image", width=300)
@@ -72,18 +72,18 @@ def classify_full_dataset(shosen_dataset_name, chosen_model_name):
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  #modle instance
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  classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
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- CONTAINER_LOOP.write("### FLAG 4")
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  #classification
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  classification_result = classifier_pipeline(image_object)
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- CONTAINER_LOOP.write(classification_result)
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- CONTAINER_LOOP.write("### FLAG 5")
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  #classification_array.append(classification_result)
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  #save classification
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  image_count += 1
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- CONTAINER_LOOP.write(f"Image count: {image_count}")
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  return image_count
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@@ -105,10 +105,10 @@ def main():
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  make_template()
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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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  # 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
@@ -116,7 +116,7 @@ def main():
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  # subprocess.call(["shutdown", "-r", "-t", "0"])
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  #with CONTAINER_BODY:
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- with CONTAINER_TOP:
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  st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
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  st.write("Soon we will have a dataset template")
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@@ -137,9 +137,9 @@ def main():
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  #classification_array =[]
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  classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
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- CONTAINER_LOOP.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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  #dataset
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  dataset = load_dataset(shosen_dataset_name,"testedata_readme")
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+ with COLS[1]:
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  #Image teste load
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  image_object = dataset['pasta'][0]["image"]
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  st.image(image_object, caption="Uploaded Image", width=300)
 
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  #modle instance
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  classifier_pipeline = pipeline('image-classification', model=chosen_model_name)
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+ COLS[1].write("### FLAG 4")
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  #classification
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  classification_result = classifier_pipeline(image_object)
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+ COLS[1].write(classification_result)
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+ COLS[1].write("### FLAG 5")
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  #classification_array.append(classification_result)
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  #save classification
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  image_count += 1
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+ COLS[1].write(f"Image count: {image_count}")
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  return image_count
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  make_template()
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+ # with CONTAINER_TOP:
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+ # st.write("# Bulk Image Classification DEMO")
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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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  # subprocess.call(["shutdown", "-r", "-t", "0"])
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  #with CONTAINER_BODY:
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+ with COLS[0]:
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  st.markdown("This app uses several 🤗 models to classify images stored in 🤗 datasets.")
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  st.write("Soon we will have a dataset template")
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  #classification_array =[]
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  classification_result = classify_full_dataset(shosen_dataset_name, chosen_model_name)
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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()