From afc5e4d3f7627171e349a79feb8a951cb03d09dd Mon Sep 17 00:00:00 2001 From: Yuren Cong <47991543+yrcong@users.noreply.github.com> Date: Mon, 1 May 2023 18:03:08 +0200 Subject: [PATCH] Update README.md --- README.md | 21 ++++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 92baf05..111e531 100644 --- a/README.md +++ b/README.md @@ -76,6 +76,12 @@ RelTR │ | train.json | | val.json | | images +│ └───oi +│ │ rel.json +│ │ test.json +│ | train.json +| | val.json +| | images └───datasets ... ``` @@ -99,11 +105,20 @@ We attached 5 images from **VG** dataset and 1 image from **internet**. You can ## Training a) Train RelTR on Visual Genome on a single node with 8 GPUs (2 images per GPU): ``` -python -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --dataset vg --img_folder data/vg/images/ --batch_size 2 --output_dir ckpt +python -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --dataset vg --img_folder data/vg/images/ --ann_path data/vg/ --batch_size 2 --output_dir ckpt +``` +b) Train RelTR on Open Images V6 on a single node with 8 GPUs (2 images per GPU): +``` +python -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --dataset oi --img_folder data/oi/images/ --ann_path data/oi/ --batch_size 2 --output_dir ckpt ``` ## Evaluation -b) Evaluate the pretrained RelTR on Visual Genome with a single GPU (1 image per GPU): +a) Evaluate the pretrained [RelTR](https://drive.google.com/file/d/1id6oD_iwiNDD6HyCn2ORgRTIKkPD3tUD/view) on Visual Genome with a single GPU (1 image per GPU): +``` +python main.py --dataset vg --img_folder data/vg/images/ --ann_path data/vg/ --eval --batch_size 1 --resume ckpt/checkpoint0149.pth +``` + +b) Evaluate the pretrained [RelTR](https://drive.google.com/file/d/1pcoUnR0XWsvM9lJZ5f93N5TKHkLdjtnb/view?usp=share_link) on Open Images V6 with a single GPU (1 image per GPU): ``` -python main.py --dataset vg --img_folder data/vg/images/ --eval --batch_size 1 --resume ckpt/checkpoint0149.pth +python main.py --dataset oi --img_folder data/oi/images/ --ann_path data/oi/ --eval --batch_size 1 --resume ckpt/checkpoint0149_oi.pth ```