Comments (2)
from dannce.
Apologies for the late reply. We have run in many different configurations, and there is no right or wrong way to set up the cameras. In the bird experiment the cameras were essentially at the walls with fisheye lenses, while in the rat experiment they were 6 feet away. Some general principles
(1) It is helpful if the animal is visible in each of the cameras at all time
(2) I would try to not use an ultrafisheye lens, as I would worry about higher order distortion terms (although to date this hasn't been a problem)
(3) The resolution in fine tuning experiments is often limited by the ability to label points by hand, so use the ability to hand label as the goal for pixel resolution.
(4) many different views and angles can work well.
let me know if I can help more!
from dannce.
Related Issues (20)
- multiple camera caliration HOT 2
- COM prediction values are NaN HOT 3
- Could not load weights for finetune (likely because you are finetuning a previously finetuned network). Attempting to finetune from a full finetune model file. HOT 18
- Zero training/validation errors but completely wrong in labeled images. HOT 2
- How to train DANNCE with more than 6 cameras? HOT 1
- COM deviate a lot from animal HOT 2
- When running dannce-predict demo script, GPU usage is at 0% HOT 1
- Integration of DANNCE and CAPTURE HOT 1
- Could not find enough inliers in imagePoints and worldPoints HOT 2
- n_views error HOT 1
- dannce-predict loss very small, but result same like normal but shift HOT 6
- Re-train network with new labeled frames HOT 1
- Multi animal COM HOT 2
- how to use rats16.mat skeleton for CAPTURE_demo analysis HOT 1
- calibration HOT 1
- OOM error HOT 2
- File "E:\anaconda\envs\tfnew_25\lib\site-packages\tensorflow\python\framework\ops.py", line 6649, in __init__ raise ValueError("name for name_scope must be a string.") HOT 1
- ValueError: name for name_scope must be a string when doing dannce-predict. HOT 1
- ValueError: bad marshal data (unknown type code) when dannce-predict HOT 1
- frames_with_good_tracking
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from dannce.