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paths.py
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""" use this python file to include direct paths to folder paths and models used """
# folder path to complete, error, and mat folder for TM and CV- ; test
folder_paths = {}
# path to move any errors caught/exceptions (training module)
folder_paths['errortm'] = r'Z:\Projects\Homecage\DLCVideos\trainingmodule_errors'
# path to save generated .MAT files (training module)
folder_paths['matfiletm'] = r'Z:\Projects\Homecage\DLCVideos\trainingmodule_matfiles'
# path to move any errors caught/exceptions (cageview)
folder_paths['errorcv'] = r'Z:\Projects\Homecage\DLC\Other\cageview_errors'
# path to save generated .MAT files (cageview)
folder_paths['matfilecv'] = r'Z:\Projects\Homecage\DLC\Other\cageview_matfiles'
# paths to different deep learning models used in analysis
modelinfo = {}
# path to custom trained OCR LSTM model
modelinfo['ocr'] = r'Z:\Projects\Homecage\DLC\VAModels\OCR\best_lstm_model/'
# deeplabcut information for training module
modelinfo['dlctm'] = {
'model_paths':
{
'black': r'Z:\Projects\Homecage\DLC\VAModels\DLC\trainingmodule\blackcoat\trainingmodule_black_v6-chenlab-2023-04-25\exported-models\DLC_trainingmodule_black_v6_mobilenet_v2_1.0_iteration-0_shuffle-1',
'white': r'Z:\Projects\Homecage\DLC\VAModels\DLC\trainingmodule\whitecoat\trainingmodule_v4_white-chenlab-2022-05-04_eval\exported-models\DLC_trainingmodule_v4_white_mobilenet_v2_0.35_iteration-0_shuffle-1',
},
'body_parts': ['nose', 'leftear', 'rightear', 'neck', 'upperback', 'lowerback', 'tail', 'tail2', 'fl_foot', 'fr_foot', 'bl_foot', 'br_foot']
}
# deeplabcut information for cage view
modelinfo['dlccv'] = {
'model_paths':
{
'blackwhite': r'Z:\Projects\Homecage\DLC\VAModels\DLC\cageview\blackwhite\cageview_v3_blackmice_white-chenlab-2022-06-27\exported-models\DLC_cageview_v3_blackmice_white_mobilenet_v2_1.0_iteration-0_shuffle-1',
'whitewhite': r'Z:\Projects\Homecage\DLC\VAModels\DLC\cageview\whitewhite\cageview_v3_whitemice_white-chenlab-2022-06-27\exported-models\DLC_cageview_v3_whitemice_white_mobilenet_v2_1.0_iteration-0_shuffle-1',
'blackred': r'Z:\Projects\Homecage\DLC\VAModels\DLC\cageview\blackred\cageview_v3_blackmice_red-chenlab-2022-06-27\exported-models\DLC_cageview_v3_blackmice_red_mobilenet_v2_1.0_iteration-0_shuffle-1',
'whitered': r'Z:\Projects\Homecage\DLC\VAModels\DLC\cageview\whitered\cageview_v3_whitemice_red-chenlab-2022-06-27\exported-models\DLC_cageview_v3_whitemice_red_mobilenet_v2_1.0_iteration-0_shuffle-1',
},
'body_parts': ['nose', 'head', 'neck', 'upperback', 'lowerback', 'tail', 'tail2']
}
# path to coat recognition model
modelinfo['coatrecognition'] = r'Z:\Projects\Homecage\DLC\VAModels\ImageClassification\trainingmodule\coatcolorclassifier\coat_classifier_weights_v8.h5'
# # path to maskrcnn training module model
# modelinfo['maskrcnntm'] = r'Z:\Projects\Homecage\DLC\VAModels\Segmentation\trainingmodule\tm_detect_03282022.h5'
modelinfo['tmdetection'] = r'Z:\Projects\Homecage\DLC\VAModels\DLC\tm-outline\tm-outline_mobilenet_v2_1.0_VERSION_2'
# path to maskrcnn cage view model
modelinfo['maskrcnncv'] = r'Z:\Projects\Homecage\DLC\VAModels\Segmentation\cageview\mask_rcnn_cage_ls_06132022.h5'
# path to led object detection model
modelinfo['objdetectLED'] = {
'model_folder_path': r'Z:\Projects\Homecage\DLC\VAModels\ObjectDetection\led\102622_yolov7',
'weights': 'yolov7_training_20000.weights',
'config': 'yolov7_training.cfg',
'trained_image_size': (416, 416),
'channels': 1
}
# location for sensitive information
sensitive_information_folder = r'Z:\Projects\Homecage\DLC\SensitiveInformation'
led_issue_info = {
# list of rigs that had LED issues (rig numbers should be integers)
'rig_led_issues': [11, 25, 10, 14, 9, 6, 23, 18, 20, 12, 13, 8, 24, 26, 15, 19, 16, 21, 25, 17, 22, 27],
# path to csv files for each rig with led issues
'led_issue_csv_paths': {
10: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_10_trial_dt.csv',
14: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_14_trial_dt.csv',
11: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_11_trial_dt.csv',
9: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_9_trial_dt.csv',
6: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_6_trial_dt.csv',
23: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_23_trial_dt.csv',
18: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_18_trial_dt.csv',
20: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_20_trial_dt.csv',
12: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_12_trial_dt.csv',
13: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_13_trial_dt.csv',
8: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_8_trial_dt.csv',
24: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_24_trial_dt.csv',
26: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_26_trial_dt.csv',
15: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_15_trial_dt.csv',
19: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_19_trial_dt.csv',
16: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_16_trial_dt.csv',
21: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_21_trial_dt.csv',
25: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_25_trial_dt.csv',
17: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_17_trial_dt.csv',
22: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_22_trial_dt.csv',
27: r'Z:\Projects\Homecage\DLC\VAModels\LedIssueFiles\Round_2\tm_27_trial_dt.csv'
}
}