It’s About Time: Analog clock Reading in the Wild
Code repository for “It’s About Time: Analog clock Reading in the Wild”
Packages required:pytorch
(used 1.9, any reasonable version should work), kornia
(for homography), einops
, scikit-learn
(for RANSAC), tensorboardX
(for logging)
Using pretrained model:
- prediction
python predict.py
will predict on your data (or by default, whatever is indata/demo
). This does assume the images being already cropped, we use CBNetv2. (you could instead add something like a yolov5 to the code if you prefer not installing anything extra). - evaluation
python eval.py
(requires dataset) should return the numbers reported in the paper
Training:
sh full_cycle.sh
should do the job- if you want to do it individually, then do use
train.py
train on SynClockgenerate_pseudo_labels.py
use the model to generate pseudo labels for timelapsetrain_refine.py
train on