This repository contains the code used for Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge 🔗 by Heitor Rapela Medeiros, Masih Aminbeidokhti, Fidel Guerrero Pena, David Latortue, Eric Granger, Marco Pedersoli (ECCV 2024).
- The code is released.
- New updates will come in the following days!
- If you find any problem or have any questions, please feel free to contact us!
conda create -n modtr python==3.8.10
pip install -r requirements.txt
# Modtr Cross with Faster R-CNN
CUDA_VISIBLE_DEVICES=0 python main.py --modality ir --wandb-project modtr --wandb-name modtr_fasterrcnn_llvip_200ep_seed123_fusecross --detector fasterrcnn --dataset llvip --epochs 200 --batch 8 --seed 123 --directly-coco --fuse-data cross
# Modtr Cross with FCOS
CUDA_VISIBLE_DEVICES=0 python main.py --modality ir --wandb-project modtr --wandb-name modtr_fcos_llvip_200ep_seed123_fusecross --detector fcos --dataset llvip --epochs 200 --batch 8 --seed 123 --directly-coco --fuse-data cross
# Modtr Cross with RetinaNet
CUDA_VISIBLE_DEVICES=0 python main.py --modality ir --wandb-project modtr --wandb-name modtr_llvip_200ep_seed123_fusecross --detector retinanet --dataset llvip --epochs 200 --batch 8 --seed 123 --directly-coco --fuse-data cross
# For flir, just change the dataset flag: --dataset flir
Thanks to the great open-source community that provided good libraries.
The code is based on our previous work HalluciDet