labelbox reupload

example.py

def delete_labels(client, label_id_list):
    res = client.execute('''
            mutation DeleteLabels($label_id_list: [ID!]) {
                deleteLabels(
                    labelIds: $label_id_list
                ){
                    id
                    deleted
                }
            }
            ''', {"label_id_list": label_id_list})
    data = json.loads(res)['data']
    return data
  
  
def relabel_keys(client, key_list, exact_model_name, df, confidence_threshold, project_id, prediction_model_id):
    """
    :param confidence_threshold: the confidence bound to add to predictions
    :param exact_model_name: the full model name
    :param key_list: A list of key strings
    :param client: labelbox client
    :param project_id: labelbox project id
    :param prediction_model_id: labelbox prediction model id
    :param df: the dataframe containing all the evaluation data
    :type df: pd.Dataframe
    """
    label_ids = []
    for key in key_list:
        response = get_label_for_key(client, key)
        print response
        if len(response) == 0:
            print "there is no labelbox label for key {} skipping".format(key)
            continue
        datarow_id = response[0]['dataRow']['id']
        for r in response:
            label_ids.append(r['id'])

        temp_df = df[
            (df['model'] == exact_model_name) & (df['key'] == key) & (
                    df['confidence'] >= confidence_threshold)]

        prediction_label = format_dataframe_for_labelbox_prediction(temp_df)
        print datarow_id
        create_prediction(client, json.dumps(prediction_label), prediction_model_id,
                          project_id, datarow_id)

    delete_labels(client, label_ids)
    
    
def create_prediction(client, label, prediction_model_id, project_id, data_row_id):
    res_str = client.execute("""
      mutation CreatePredictionFromAPI($label: String!, $predictionModelId: ID!, $projectId: ID!, $dataRowId: ID!) {
        createPrediction(data:{
          label: $label,
          predictionModelId: $predictionModelId,
          projectId: $projectId,
          dataRowId: $dataRowId,
        }){
          id
        }
      }
    """, {
        'label': label,
        'predictionModelId': prediction_model_id,
        'projectId': project_id,
        'dataRowId': data_row_id
    })

    res = json.loads(res_str)
    return res['data']['createPrediction']['id']