/CS555-project

Object Detection using Domain Randomized Data

Primary LanguagePython

Framework for training a neural network model for object detection in 2d image

Getting started

Dataset

Make sure your dataset folder is in following order.

dataset
├── train        
│   ├── images          # raw images
│   ├── labels          # bbox label files
└── test
│   ├── images          # raw images
│   ├── labels          # bbox label files
└── valid
│   ├── images          # raw images
│   ├── labels          # bbox label files
└── models              # directory to save the checkpoints 
│   ├── ...             # saved checkpoints
└── tensorboard_logs    # directory to save tensorboard logs
    ├── ...             # saved logs

Please create models and tensorboard_logs directories if they don't exist.
Make sure your image file name and label file name is same i.e., if image file name is some_image.png then corresponding label file would be some_image.txt

Run

Distributed

python -m torch.distributed.launch --nproc_per_node=<number_of_avaliable_GPUs> train.py 
--data <path_to_dataset_folder> --batch-size <N int> --log-dir <tensorboard_logs_folder> --save-as <filename>

Single GPU

python train.py 
--data <path_to_dataset_folder> --batch-size <N int> --log-dir <tensorboard_logs_folder> --save-as <filename>

References

Object Detection PyTorch
ImageNet PyTorch example