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 in data/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 SynClock
  • generate_pseudo_labels.py use the model to generate pseudo labels for timelapse
  • train_refine.py train on

     

     

     

    To finish reading, please visit source site