Nikesh Devkota
Nikesh Devkota
The original version of CUDA is not compatible with the GPU I am using in Linux , so it doesn't work in my case.
I will do that and check if there is any improvement. Is there any other way to find the optimal tracking thresholds besides manually changing it with presumption?
Hi, I tried to use Visdom to visualize the training and evaluation metrics as suggested in the documents, but the Visdom server is showing a blank blue screen.  I...
   I managed to load results from visdom. BUt I still can't figure out why the tracking woks on validation data but not the test data. @timmeinhardt
I managed to load val_dataset for tracking during training and then do tracking for test data separately. If you generated COCO annotations from "src/generate_coco_from_mot17.py," for the whole training data and...
I tracked separate cross-validation data during the training phase. After the whole training was completed, I used the optimal MOTA model for tracking separate test data. If your original train...
@insookim43 did you change the code and evaluated the test data?