Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
First of all, thanks a lot for this nice contribution!
I encountered a problem when predicting new datasets. When I run this command:
data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.main.run(PREDICT_FOLDERS)
There is an "IndexError".
In [3]: data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.main.run(PRE
...: DICT_FOLDERS)
Well, I did not copy the processed here.
IndexError Traceback (most recent call last)
in
----> 1 data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.main.run(PREDICT_FOLDERS)
~/Software/Deep Learning/B-SOiD/bsoid_py/main.py in run(predict_folders)
62 with open(os.path.join(OUTPUT_PATH, str.join('', ('bsoid_', MODEL_NAME, '.sav'))), 'rb') as fr:
63 behv_model, scaler = joblib.load(fr)
---> 64 data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.classify.main(predict_folders, scaler, FPS, behv_model)
65 filenames = []
66 all_df = []
~/Software/Deep Learning/B-SOiD/bsoid_py/classify.py in main(predict_folders, scaler, fps, behv_model)
167 plot_feats(feats_new, labels_fslow)
168 if GEN_VIDEOS:
--> 169 videoprocessing.main(VID_NAME, labels_fslow[ID], FPS, FRAME_DIR)
170 return data_new, feats_new, labels_fslow, labels_fshigh
~/Software/Deep Learning/B-SOiD/bsoid_py/utils/videoprocessing.py in main(vidname, labels, fps, output_path)
154 def main(vidname, labels, fps, output_path):
155 vid2frame(vidname, labels, fps, output_path)
--> 156 create_labeled_vid(labels, crit=3, counts=5, frame_dir=output_path, output_path=SHORTVID_DIR)
157 return
158
~/Software/Deep Learning/B-SOiD/bsoid_py/utils/videoprocessing.py in create_labeled_vid(labels, crit, counts, frame_dir, output_path)
121 sort_nicely(images)
122 fourcc = cv2.VideoWriter_fourcc(*'mp4v')
--> 123 frame = cv2.imread(os.path.join(frame_dir, images[0]))
124 height, width, layers = frame.shape
125 rnges = []
IndexError: list index out of range
Where is the problem? Is this because the DIR path is too long?
Thank you very much!
First of all, thanks a lot for this nice contribution!
I encountered a problem when predicting new datasets. When I run this command: data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.main.run(PREDICT_FOLDERS)
There is an "IndexError".
In [3]: data_new, feats_new, labels_fslow, labels_fshigh = bsoid_py.main.run(PRE ...: DICT_FOLDERS)
Well, I did not copy the processed here.
IndexError Traceback (most recent call last)