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- import sys
- import os
- import random
- import numpy as np
- import shutil
- sys.path.append("/home/shanwei-luo/userdata/mmdetection")
- from mmdet.apis import (async_inference_detector, inference_detector,
- init_detector, show_result_pyplot)
-
- config_file_1 = '/home/shanwei-luo/userdata/mmdetection/work_dirs/AD_dsxw_test70/AD_dsxw_test70.py'
- checkpoint_file_1 = '/home/shanwei-luo/userdata/mmdetection/work_dirs/AD_dsxw_test70/epoch_38.pth'
-
- img_path = '/home/shanwei-luo/userdata/datasets/PCBA_dataset_v15_MLOPS/ok/'
- dis_path = '/home/shanwei-luo/userdata/datasets/PCBA_dataset_v15_MLOPS/v3_finetune/dsxw_train/images/'
-
-
- imgs = os.listdir(img_path)
- imgs_name = []
- for img in imgs:
- imgs_name.append(img_path+img)
-
- np_result = np.load('/home/shanwei-luo/userdata/datasets/PCBA_dataset_v15_MLOPS/result.npy')
- result_score = np_result.tolist()
- for k_v in np.arange(0.05, 0.1, 0.005):
- count = 0
- index = 0
- k_v = 0.07
- for result in result_score:
- if result>=k_v:
- shutil.copy(img_path+imgs[index], dis_path+imgs[index])
- count +=1
- print(count)
- index += 1
- print(k_v, count)
- break
- imgs = os.listdir(dis_path)
- print(len(imgs))
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