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- import sys
- import os
- import random
- sys.path.append("/home/shanwei-luo/userdata/mmdetection")
- from mmdet.apis import (async_inference_detector, inference_detector,
- init_detector, show_result_pyplot)
-
- class_AOI_name = {"bu_pi_pei":"1","fang_xiang_fan":"2","err.txt_c_not_f":"3", "shang_xi_bu_lia":"4"}
-
- config_file_1 = '/home/shanwei-luo/userdata/mmdetection/work_dirs/AD_dsxw_test61/AD_dsxw_test61.py'
- checkpoint_file_1 = '/home/shanwei-luo/userdata/mmdetection/work_dirs/AD_dsxw_test61/epoch_36.pth'
- model_1 = init_detector(config_file_1, checkpoint_file_1, device='cuda:0')
-
- dirs_path = '/home/shanwei-luo/userdata/datasets/dsxw_test_SMD12_2022_0301_0314_day/'
- dirs_name = os.listdir(dirs_path)
- for dir_name in dirs_name:
- imgs_ok_path = dirs_path+dir_name+"/ok/"
- imgs_ng_path = dirs_path+dir_name+"/ng/"
-
- imgs_ok = os.listdir(imgs_ok_path)
- imgs_ng = os.listdir(imgs_ng_path)
-
- count_label_ok = len(imgs_ok)
- count_label_ng = len(imgs_ng)
- #print(count_label_ok,count_label_ng)
- imgs_labels = []
- imgs_name = []
- for img in imgs_ok:
- img_name = img.split("@")
- if img_name[2] in class_AOI_name.keys():
- count_label_ok -= 1
- continue
- imgs_labels.append(0)
- imgs_name.append(imgs_ok_path+img)
-
- for img in imgs_ng:
- img_name = img.split("@")
- if img_name[2] in class_AOI_name.keys():
- count_label_ng -= 1
- continue
- imgs_labels.append(1)
- imgs_name.append(imgs_ng_path+img)
-
- #print(count_label_ok,count_label_ng, len(imgs_labels))
- #print("before infer")
- index = 0
- num = len(imgs_name)
- results_1 = []
- step = 256
- while index<num:
- index += step
- if index < num:
- results_1_tmp = inference_detector(model_1, imgs_name[index-step:index])
- else:
- results_1_tmp = inference_detector(model_1, imgs_name[index-step:num])
- results_1 += results_1_tmp
- #print("after infer")
-
- imgs_results_1 = []
- for result in results_1:
- res_predict = 0
- for i in result:
- for j in range(i.shape[0]):
- if i[j, 4]>0.015:
- res_predict = 1
- imgs_results_1.append(res_predict)
-
- count_ng = 0
- count_ok = 0
- for i in range(len(imgs_labels)):
- if imgs_labels[i]==0 and imgs_results_1[i]==0:
- count_ok += 1
- if imgs_labels[i]==1 and imgs_results_1[i]==1:
- count_ng += 1
- if imgs_labels[i]==1 and imgs_results_1[i]==0:
- print(imgs_name[i])
- print(count_label_ok,count_label_ng)
- print(count_ok/count_label_ok, count_ng/count_label_ng)
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