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- import pandas as pd
- import os
- import shutil
-
- source_path = '/home/shanwei-luo/teamdata/anomaly_detection_active_learning/data0422/unlabel_11_12/'
- dist_path_01 = '/home/shanwei-luo/teamdata/anomaly_detection_active_learning/data0422/smd12_11_12_hard_score_01/train/'
- dist_path_02 = '/home/shanwei-luo/teamdata/anomaly_detection_active_learning/data0422/smd12_11_12_hard_score_02/train/'
- infer_data=pd.read_csv('./test_unlabel_11_12.csv')
- print(infer_data.shape)
-
- infer_data.info()
- infer_data.describe()
- infer_data.head()
-
- print(infer_data['score'])
- print(infer_data['Image_Name'])
- infer_data = infer_data.sort_values('score',ascending=False)
- select_01 = []
- select_02 = []
- for index, row in infer_data.iterrows():
- #print(row['Image_Name'], row['score'])
- if len(select_01) < 2750:
- select_01.append(row['Image_Name'])
- if row['score']<0.85 and len(select_02)<2750:
- select_02.append(row['Image_Name'])
-
- print(len(select_01))
- print(len(select_02))
-
- count_img = 0
- count_label = 0
- for file in select_01:
- shutil.copy(source_path+'images/'+file, dist_path_01+'images/'+file)
- count_img += 1
- if os.path.exists(source_path+'labels/'+file.replace(".jpg",".txt")):
- shutil.copy(source_path+'labels/'+file.replace(".jpg",".txt"), dist_path_01+'labels/'+file.replace(".jpg",".txt"))
- count_label += 1
- print(count_img, count_label)
-
- count_img = 0
- count_label = 0
- for file in select_02:
- shutil.copy(source_path+'images/'+file, dist_path_02+'images/'+file)
- count_img += 1
- if os.path.exists(source_path+'labels/'+file.replace(".jpg",".txt")):
- shutil.copy(source_path+'labels/'+file.replace(".jpg",".txt"), dist_path_02+'labels/'+file.replace(".jpg",".txt"))
- count_label += 1
- print(count_img, count_label)
-
- '''print(len(infer_data['feature'][0]))
- feat = infer_data['feature'][0].split(",")
- print(len(feat))
- print(feat[0])'''
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