step6_predict_nodules_validation.py 文件源码

def merge_csv_orign():
    df_empty = pandas.DataFrame(columns=['seriesuid','coord_x','coord_y','coord_z','probability',])
    src_dir =settings.VAL_NODULE_DETECTION_DIR+'predictions10_luna16_fs/'
    # src_dir =settings.VAL_NODULE_DETECTION_DIR
    # for r in glob.glob(src_dir + "*_candidates_1.csv"):
    for r in glob.glob(src_dir + "*.csv"):
        csv=pandas.read_csv(r)
        del csv['diameter']
        del csv['diameter_mm']
        del csv['anno_index']
        file_name = ntpath.basename(r)
        # patient_id = file_name.replace("_candidates_1.csv", "")
        patient_id = file_name.replace(".csv", "")
        csv['seriesuid']=patient_id
        csv = csv[csv["probability"] >= 0.95]
        df_empty = df_empty.append(csv)
    id = df_empty['seriesuid']
    df_empty.drop(labels=['seriesuid'], axis=1,inplace = True)
    df_empty.insert(0, 'seriesuid', id)
    df_empty.rename(columns={'coord_x':'coordX','coord_y':'coordY','coord_z':'coordZ'}, inplace = True)
    df_empty.to_csv("./output_val/prediction_can_val3.csv",index=False)