Describe the bug
During refinement, after uploading the video and pose file, the software returns "terminated early" for some videos and cannot extract frames. The software is able to extract frames for some videos but fails to generate refinement sets that can be reviewed, with the 'nonetype' object is not subscriptable error message.
Error message as follows (also shown in screenshot):
TypeError: 'NoneType' object is not subscriptable
Traceback:
File "C:\Users\buczy\anaconda3\envs\asoid\lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 584, in _run_script
exec(code, module.dict)
File "C:\Users\buczy\Desktop\A-SOID-main\asoid\app.py", line 328, in
main()
File "C:\Users\buczy\Desktop\A-SOID-main\asoid\app.py", line 307, in main
D_manual_active_learning.main(ri=ri, config=st.session_state['config'])
File "c:\users\buczy\desktop\a-soid-main\asoid\apps\D_manual_active_learning.py", line 33, in main
refinement.main()
File "c:\users\buczy\desktop\a-soid-main\asoid\utils\manual_refinement.py", line 912, in main
(st.session_state['examples_idx'][behav_choice][i][1] -
To Reproduce
Steps to reproduce the behavior:
Go to 'Refine behaviors', upload video and corresponding pose file
Go to 'Create New Data Set'
Create Dataset
Go to 'Active Learning'
Start Active learning > error is generated
Expected behavior
Expected refinement sets to be generated and to be able to provide user feedback, in order to train the system further.
Screenshots
Desktop (please complete the following information):
Describe the bug During refinement, after uploading the video and pose file, the software returns "terminated early" for some videos and cannot extract frames. The software is able to extract frames for some videos but fails to generate refinement sets that can be reviewed, with the 'nonetype' object is not subscriptable error message.
Error message as follows (also shown in screenshot):
To Reproduce Steps to reproduce the behavior:
Expected behavior Expected refinement sets to be generated and to be able to provide user feedback, in order to train the system further.
Screenshots
Desktop (please complete the following information):
Project Config (please post the content of the corresponding config.ini file) [Project] PROJECT_TYPE = DeepLabCut PROJECT_NAME = May-26-2024_editedBORIS PROJECT_PATH = C:\Users\buczy/Desktop/asoid_output FRAMERATE = 60 KEYPOINTS_CHOSEN = Nose, BetweenEyes, LeftEar, RightEar, Neck, LeftShoulder, RightShoulder, BodyCentre, LeftSide, RightSide, LeftHip, RightHip, TailBase, TailCentre, TailTip EXCLUDE_OTHER = False FILE_TYPE = csv INDIVIDUALS_CHOSEN = single animal CLASSES = Dig, Genital/Stomach Groom, Head Groom, Jump, Rear, Scratch, Shake, Side/Back Groom, Stand, Tail Rigid, other MULTI_ANIMAL = False IS_3D = False
[Data] DATA_INPUT_FILES = 042524_CS_T8_T_I2DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042524_CS_T8_T_J4DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042624_CS_T8_T_L1DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042524_CS_T8_T_A4DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042524_CS_T8_T_A3DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042524_CS_T8_T_A5DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv, 042524_CS_T8_T_B2DLC_resnet50_SomaticVideoMar28shuffle4_200000_filtered.csv LABEL_INPUT_FILES = CIE 2_No focal subject.csv, CIE 4_No focal subject.csv, CIE 6_No focal subject.csv, CIE 9_No focal subject.csv, CIE 21_No focal subject.csv, CIE 30_No focal subject.csv, CIE 33_No focal subject.csv ROOT_PATH = None
[Processing] LLH_VALUE = 0.1 ITERATION = 0 MIN_DURATION = 0.1 TRAIN_FRACTION = 0.65 MAX_ITER = 1000 MAX_SAMPLES_ITER = 110 CONF_THRESHOLD = 0.5 N_SHUFFLED_SPLIT = None
Additional context