From 3ba53bab4e4ee9e914afdb11ea4d414ad5f25b6e Mon Sep 17 00:00:00 2001 From: Ren Tianhe <48727989+rentainhe@users.noreply.github.com> Date: Tue, 18 Oct 2022 18:51:55 +0800 Subject: [PATCH] Release detrex v0.1.1 (#104) * refine README * release v0.1.1 * refine README * refine Deformable-DETR README * refine README Co-authored-by: ntianhe ren --- README.md | 22 +++++++++++----------- changlog.md | 15 +++++++++++++++ docs/source/changelog.md | 15 +++++++++++++++ projects/deformable_detr/README.md | 2 +- setup.py | 2 +- 5 files changed, 43 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index 9f5fc3da..0f313d6a 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ [🛠️Installation](https://detrex.readthedocs.io/en/latest/tutorials/Installation.html) | [👀Model Zoo](https://detrex.readthedocs.io/en/latest/tutorials/Model_Zoo.html) | [🚀Awesome DETR](https://github.com/IDEA-Research/awesome-detection-transformer) | -[🆕News](#change-log) | +[🆕News](#whats-new) | [🤔Reporting Issues](https://github.com/IDEA-Research/detrex/issues/new/choose) @@ -53,6 +53,16 @@ The repo name detrex has several interpretations: - de-t.rex : de means 'the' in Dutch. T.rex, also called Tyrannosaurus Rex, means 'king of the tyrant lizards' and connects to our research work 'DINO', which is short for Dinosaur. +## What's New +v0.1.1 was released on 18/10/2022: +- Add model analysis tools and benchmark in [tools](./tools/). +- Support visualization on COCO eval results and annotations in [tools](./tools/) +- Support [Group-DETR](./projects/group_detr/). +- Release more DINO training results including `DINO-R50-24epochs`, `DINO-R101`, `DINO-Swin-Tiny`, `DINO-Swin-Small`, `DINO-Swin-Base`, `DINO-Swin-Large` in [DINO](./projects/dino/). +- Release better `Deformable-DETR` baselines with **48.2 AP** on COCO dataset in [Deformable-DETR](./projects/deformable_detr/). + + +Please see [changelog.md](./changlog.md) for details and release history. ## Installation @@ -87,16 +97,6 @@ Please see [projects](./projects/) for the details about projects that are built -## Change Log - -The **beta v0.1.0** version was released in 21/09/2022. Highlights of the released version: -- Support various backbones, including: [FocalNet](https://arxiv.org/abs/2203.11926), [Swin-T](https://arxiv.org/pdf/2103.14030.pdf), [ResNet](https://arxiv.org/abs/1512.03385) and other [detectron2 builtin backbones](https://github.com/facebookresearch/detectron2/tree/main/detectron2/modeling/backbone). -- Add [timm](https://github.com/rwightman/pytorch-image-models) backbone wrapper and [torchvision](https://github.com/pytorch/vision) backbone wrapper. -- Support various Transformer-based detection algorithms, including: [DETR](https://arxiv.org/abs/2005.12872), [Deformable-DETR](https://arxiv.org/abs/2010.04159), [Conditional-DETR](https://arxiv.org/abs/2108.06152), [DAB-DETR](https://arxiv.org/abs/2201.12329), [DN-DETR](https://arxiv.org/abs/2203.01305), and [DINO](https://arxiv.org/abs/2203.03605). -- Support flexible config system based on [Lazy Configs](https://detectron2.readthedocs.io/en/latest/tutorials/lazyconfigs.html) - -Please see [changelog.md](./changlog.md) for details and release history. - ## License This project is released under the [Apache 2.0 license](LICENSE). diff --git a/changlog.md b/changlog.md index 54eaebe2..075e9698 100644 --- a/changlog.md +++ b/changlog.md @@ -1,5 +1,20 @@ ## Change Log +### v0.1.1 (18/10/2022) +#### New Features +- Add model analyze tools for detrex [#79](https://github.com/IDEA-Research/detrex/pull/79) +- Add benchmark [#81](https://github.com/IDEA-Research/detrex/pull/81) +- Add visualization for COCO eval results and annotations [#82](https://github.com/IDEA-Research/detrex/pull/82) +- Support `Group-DETR` algorhtim [#84](https://github.com/IDEA-Research/detrex/pull/84) +- Release `DINO-Swin` training results [#86](https://github.com/IDEA-Research/detrex/pull/86) +- Release better `Deformable-DETR` baselines [#102](https://github.com/IDEA-Research/detrex/pull/102) [#103](https://github.com/IDEA-Research/detrex/pull/103) + +#### Bug Fixes +- Fix bugs in ConvNeXt backbone [#91](https://github.com/IDEA-Research/detrex/pull/91) + +#### Documentation +- Add pretrained model weights download links [#86](https://github.com/IDEA-Research/detrex/pull/86) + ### v0.1.0 (30/09/2022) The **beta v0.1.0** version of detrex was released in 30/09/2022 diff --git a/docs/source/changelog.md b/docs/source/changelog.md index cf9a7ad6..edbf44e7 100644 --- a/docs/source/changelog.md +++ b/docs/source/changelog.md @@ -1,5 +1,20 @@ ## Change Log +### v0.1.1 (18/10/2022) +#### New Features +- Add model analyze tools for detrex [#79](https://github.com/IDEA-Research/detrex/pull/79) +- Add benchmark [#81](https://github.com/IDEA-Research/detrex/pull/81) +- Add visualization for COCO eval results and annotations [#82](https://github.com/IDEA-Research/detrex/pull/82) +- Support `Group-DETR` algorhtim [#84](https://github.com/IDEA-Research/detrex/pull/84) +- Release `DINO-Swin` training results [#86](https://github.com/IDEA-Research/detrex/pull/86) +- Release better `Deformable-DETR` baselines [#102](https://github.com/IDEA-Research/detrex/pull/102) [#103](https://github.com/IDEA-Research/detrex/pull/103) + +#### Bug Fixes +- Fix bugs in ConvNeXt backbone [#91](https://github.com/IDEA-Research/detrex/pull/91) + +#### Documentation +- Add pretrained model weights download links [#86](https://github.com/IDEA-Research/detrex/pull/86) + ### v0.1.0 (21/09/2022) The **beta v0.1.0** version of detrex was released in 21/09/2022 diff --git a/projects/deformable_detr/README.md b/projects/deformable_detr/README.md index e9cc22fe..03a65290 100644 --- a/projects/deformable_detr/README.md +++ b/projects/deformable_detr/README.md @@ -41,7 +41,7 @@ Here we provide the pretrained `Deformable-DETR` weights based on detrex. All the models are trained using `8 GPUs` with total batch size equals to `16`. We've observed that the result of `deformable-two-stage` model trained using `8 GPUs` may be slightly lower than `16 GPUs` with `32` total batch size. -**Notable facts and caveats**: The training settings are different from the original repo, we use `lr=1e-5` for backbone and `1e-4` for the other modules. The original implementation sets `lr` to `2e-5` for `backbone`, `sampling_offsets` and `reference_points`, and `2e-4` for other modules. And we used `top-300` confidence boxes for testing, which may get a slightly better results on COCO evaluation. And we only freeze the stem layer in ResNet backbone by setting `freeze_at=1` in config. +**Notable facts and caveats**: The training settings are different from the original repo. Most of the training settings are following [DINO](https://github.com/IDEA-Research/detrex/tree/main/projects/dino). As we set `lr=1e-5` for backbone and `1e-4` for the other modules. The original implementation sets `lr` to `2e-5` for `backbone`, `sampling_offsets` and `reference_points`, and `2e-4` for other modules. And we used `top-300` confidence boxes for testing, which may get a slightly better results on COCO evaluation. And we only freeze the stem layer in ResNet backbone by setting `freeze_at=1` in config. ## Converted Weights diff --git a/setup.py b/setup.py index 256b9e6f..9216676b 100644 --- a/setup.py +++ b/setup.py @@ -31,7 +31,7 @@ from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension # detrex version info -version = "0.1.0" +version = "0.1.1" package_name = "detrex" cwd = os.path.dirname(os.path.abspath(__file__))