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这个代码仓库是[InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions](https://arxiv.org/abs/2211.05778)的官方实现。 这个代码仓库是[InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions](https://arxiv.org/abs/2211.05778)的官方实现。
[文章](https://arxiv.org/abs/2211.05778) \| [博客](https://zhuanlan.zhihu.com/p/610772005) | [文档](./docs/) [论文](https://arxiv.org/abs/2211.05778) \| [知乎专栏](https://zhuanlan.zhihu.com/p/610772005) | [文档](./docs/)
## 简介 ## 简介
商汤科技与上海人工智能实验室在2023年3月14日联合发布多模态多任务通用大模型“书生2.5”。“书生2.5”在多模态多任务处理能力中斩获多项全新突破，其卓越的图文跨模态任务处理能力可为自动驾驶等通用场景任务提供高效精准的感知和理解能力支持。“书生2.5”致力于多模态多任务通用模型的构建，旨在接收处理各种不同模态的输入，并采用统一的模型架构和参数处理各种不同的任务，促进不同模态和任务之间在表示学习方面的协作，逐步实现通用人工智能领域的融会贯通。 商汤科技与上海人工智能实验室在2023年3月14日联合发布多模态多任务通用大模型“书生2.5”。“书生2.5”在多模态多任务处理能力中斩获多项全新突破，其卓越的图文跨模态任务处理能力可为自动驾驶等通用场景任务提供高效精准的感知和理解能力支持。“书生2.5”致力于多模态多任务通用模型的构建，旨在接收处理各种不同模态的输入，并采用统一的模型架构和参数处理各种不同的任务，促进不同模态和任务之间在表示学习方面的协作，逐步实现通用人工智能领域的融会贯通。
...@@ -48,7 +48,7 @@ ...@@ -48,7 +48,7 @@
- 2023年2月28日: 🚀 InternImage 被CVPR 2023接收! - 2023年2月28日: 🚀 InternImage 被CVPR 2023接收!
- 2022年11月18日: 🚀 基于 InternImage-XL 主干网络，[BEVFormer v2](https://arxiv.org/abs/2211.10439) 在nuScenes的纯视觉3D检测任务上取得了最佳性能 `63.4 NDS` ！ - 2022年11月18日: 🚀 基于 InternImage-XL 主干网络，[BEVFormer v2](https://arxiv.org/abs/2211.10439) 在nuScenes的纯视觉3D检测任务上取得了最佳性能 `63.4 NDS` ！
- 2022年11月10日: 🚀 InternImage-H 在COCO目标检测任务上以 `65.4 mAP` 斩获冠军，是唯一突破 `65.0 mAP` 的超强物体检测模型！ - 2022年11月10日: 🚀 InternImage-H 在COCO目标检测任务上以 `65.4 mAP` 斩获冠军，是唯一突破 `65.0 mAP` 的超强物体检测模型！
- 2022年11月10日: 🚀 InternImage-H 在ADE20k语义分割数据集上取得 `62.9 mIoU` 的SOTA性能！ - 2022年11月10日: 🚀 InternImage-H 在ADE20K语义分割数据集上取得 `62.9 mIoU` 的SOTA性能！
## “书生2.5”的应用 ## “书生2.5”的应用
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<th>COCO</th><th>VOC 2007</th><th>VOC 2012</th><th>OpenImage</th><th>LVIS minival</th><th>LVIS val</th><th>BDD100K</th><th>nuScenes</th><th>CrowdHuman</th> <th>COCO</th><th>VOC 2007</th><th>VOC 2012</th><th>OpenImage</th><th>LVIS minival</th><th>LVIS val</th><th>BDD100K</th><th>nuScenes</th><th>CrowdHuman</th>
</tr> </tr>
<tr align="center"> <tr align="center">
<th>65.5</th><th>94.0</th><th>97.2</th><th>74.1</th><th>62.5</th><th>63.2</th><th>38.8</th><th>64.8</th><th>97.2</th> <th>65.5</th><th>94.0</th><th>97.2</th><th>74.1</th><th>65.8</th><th>63.2</th><th>38.8</th><th>64.8</th><th>97.2</th>
</tr> </tr>
</table> </table>
<br> <br>
...@@ -149,14 +149,14 @@ ...@@ -149,14 +149,14 @@
## 项目功能 ## 项目功能
- [ ] 各类downstream tasks - [ ] 各类下游任务
- [x] InternImage-H(1B)/G(3B) - [x] InternImage-H(1B)/G(3B)
- [x] TensorRT 推理 - [x] TensorRT 推理
- [x] InternImage系列分类代码 - [x] InternImage 系列分类代码
- [x] InternImage-T/S/B/L/XL ImageNet-1k 预训练模型 - [x] InternImage-T/S/B/L/XL ImageNet-1K 预训练模型
- [x] InternImage-L/XL ImageNet-22k 预训练模型 - [x] InternImage-L/XL ImageNet-22K 预训练模型
- [x] InternImage-T/S/B/L/XL 检测和实例分割模型 - [x] InternImage-T/S/B/L/XL 检测和实例分割模型
- [x] InternImage-T/S/B/L/XL语义分割模型 - [x] InternImage-T/S/B/L/XL 语义分割模型
## 开源模型 ## 开源模型
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| InternImage-B | ImageNet-1K | 224x224 | 84.9 | 97M | 16G | - | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_b_1k_224.pth) \| [cfg](classification/configs/internimage_b_1k_224.yaml) | | InternImage-B | ImageNet-1K | 224x224 | 84.9 | 97M | 16G | - | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_b_1k_224.pth) \| [cfg](classification/configs/internimage_b_1k_224.yaml) |
| InternImage-L | ImageNet-22K | 384x384 | 87.7 | 223M | 108G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_l_22k_192to384.pth) | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_l_22kto1k_384.pth) \| [cfg](classification/configs/internimage_l_22kto1k_384.yaml) | | InternImage-L | ImageNet-22K | 384x384 | 87.7 | 223M | 108G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_l_22k_192to384.pth) | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_l_22kto1k_384.pth) \| [cfg](classification/configs/internimage_l_22kto1k_384.yaml) |
| InternImage-XL | ImageNet-22K | 384x384 | 88.0 | 335M | 163G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_xl_22k_192to384.pth) | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_xl_22kto1k_384.pth) \| [cfg](classification/configs/internimage_xl_22kto1k_384.yaml) | | InternImage-XL | ImageNet-22K | 384x384 | 88.0 | 335M | 163G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_xl_22k_192to384.pth) | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/cls_model/internimage_xl_22kto1k_384.pth) \| [cfg](classification/configs/internimage_xl_22kto1k_384.yaml) |
| InternImage-H | Joint 427M | 224x224 | 88.9 | 1.08B | 188G | - | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_h_jointto1k_224.yaml) | | InternImage-H | Joint 427M | 224x224 | 88.9 | 1.08B | 188G | TBD | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_h_jointto1k_224.yaml) |
| InternImage-H | Joint 427M | 640x640 | 89.6 | 1.08B | 1478G | - | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_h_jointto1k_640.yaml) | | InternImage-H | Joint 427M | 640x640 | 89.6 | 1.08B | 1478G | TBD | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_h_jointto1k_640.yaml) |
| InternImage-G | Joint 427M | 512x512 | 90.1 | 3B | - | - | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_g_jointto1k_512.yaml) | | InternImage-G | Joint 427M | 512x512 | 90.1 | 3B | TBD | TBD | [ckpt](https://pan.baidu.com/s/1R3niTRjrERUet2xGc6ePPA) \| [cfg](classification/configs/internimage_g_jointto1k_512.yaml) |
- Extraction code for downloading InternImage-H/G: 2vwu - 下载InternImage-H/G的百度网盘提取码: 2vwu
**COCO目标检测和实例分割** **COCO目标检测和实例分割**
| backbone | method | schd | box mAP (val/test) | mask mAP (val/test) | #param | FLOPs | Download | | backbone | method | schd | box mAP | mask mAP | #param | FLOPs | Download |
| :------------: | :----------------: | :---------: | :-----: | :------: | :-----: | :---: | :---: | | :------------: | :----------------: | :---------: | :-----: | :------: | :-----: | :---: | :---: |
| InternImage-T | Mask R-CNN | 1x | 47.2/- | 42.5/- | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_1x_coco.py) | | InternImage-T | Mask R-CNN | 1x | 47.2 | 42.5 | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_1x_coco.py) |
| InternImage-T | Mask R-CNN | 3x | 49.1/- | 43.7/- | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_3x_coco.py) | | InternImage-T | Mask R-CNN | 3x | 49.1 | 43.7 | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_3x_coco.py) |
| InternImage-S | Mask R-CNN | 1x | 47.8/- | 43.3/- | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_1x_coco.py) | | InternImage-S | Mask R-CNN | 1x | 47.8 | 43.3 | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_1x_coco.py) |
| InternImage-S | Mask R-CNN | 3x | 49.7/- | 44.5/- | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_3x_coco.py) | | InternImage-S | Mask R-CNN | 3x | 49.7 | 44.5 | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_3x_coco.py) |
| InternImage-B | Mask R-CNN | 1x | 48.8/- | 44.0/- | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_1x_coco.py) | | InternImage-B | Mask R-CNN | 1x | 48.8 | 44.0 | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_1x_coco.py) |
| InternImage-B | Mask R-CNN | 3x | 50.3/- | 44.8/- | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_3x_coco.py) | | InternImage-B | Mask R-CNN | 3x | 50.3 | 44.8 | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_3x_coco.py) |
| InternImage-L | Cascade | 1x | 54.9/- | 47.7/- | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_1x_coco.py) | | InternImage-L | Cascade | 1x | 54.9 | 47.7 | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_1x_coco.py) |
| InternImage-L | Cascade | 3x | 56.1/- | 48.5/- | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_3x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_3x_coco.py) | | InternImage-L | Cascade | 3x | 56.1 | 48.5 | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_3x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_3x_coco.py) |
| InternImage-XL | Cascade | 1x | 55.3/- | 48.1/- | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_1x_coco.py) | | InternImage-XL | Cascade | 1x | 55.3 | 48.1 | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_1x_coco.py) |
| InternImage-XL | Cascade | 3x | 56.2/- | 48.8/- | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_3x_coco.py) | | InternImage-XL | Cascade | 3x | 56.2 | 48.8 | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_3x_coco.py) |
| InternImage-H | DINO (TTA) | 3x | 65.0/65.4 | -/- | 2.18B | TBD | TBD |
| InternImage-G | DINO (TTA) | 3x | 65.3/65.5 | -/- | 3B | TBD | TBD | | backbone | method | box mAP (val/test) | #param | FLOPs | Download |
| :------------: | :----------------: | :---------: | :------: | :-----: | :---: |
| InternImage-H | DINO (TTA) | 65.0 / 65.4 | 2.18B | TBD | TBD |
| InternImage-G | DINO (TTA) | 65.3 / 65.5 | 3B | TBD | TBD |
**ADE20K语义分割** **ADE20K语义分割**
| backbone | resolution | single scale | multi scale | #param | FLOPs | Download | | backbone | method | resolution | mIoU (ss/ms) | #param | FLOPs | Download |
| :------------: | :--------: | :----------: | :---------: | :-----: | :---: | :---: | | :------------: | :--------: | :--------: | :----------: | :-----: | :---: | :---: |
| InternImage-T | 512x512 | 47.9 | 48.1 | 59M | 944G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_t_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_t_512_160k_ade20k.py) | | InternImage-T | UperNet | 512x512 | 47.9 / 48.1 | 59M | 944G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_t_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_t_512_160k_ade20k.py) |
| InternImage-S | 512x512 | 50.1 | 50.9 | 80M | 1017G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_s_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_s_512_160k_ade20k.py) | | InternImage-S | UperNet | 512x512 | 50.1 / 50.9 | 80M | 1017G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_s_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_s_512_160k_ade20k.py) |
| InternImage-B | 512x512 | 50.8 | 51.3 | 128M | 1185G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_b_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_b_512_160k_ade20k.py) | | InternImage-B | UperNet | 512x512 | 50.8 / 51.3 | 128M | 1185G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_b_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_b_512_160k_ade20k.py) |
| InternImage-L | 640x640 | 53.9 | 54.1 | 256M | 2526G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_l_640_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_l_640_160k_ade20k.py) | | InternImage-L | UperNet | 640x640 | 53.9 / 54.1 | 256M | 2526G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_l_640_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_l_640_160k_ade20k.py) |
| InternImage-XL | 640x640 | 55.0 | 55.3 | 368M | 3142G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_xl_640_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_xl_640_160k_ade20k.py) | | InternImage-XL | UperNet | 640x640 | 55.0 / 55.3 | 368M | 3142G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_xl_640_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_xl_640_160k_ade20k.py) |
| InternImage-H | 896x896 | 59.9 | 60.3 | 1.12B | 3566G | TBD | | InternImage-H | UperNet | 896x896 | 59.9 / 60.3 | 1.12B | 3566G | TBD |
| InternImage-H | 896x896 | 62.5 | 62.9 | 1.31B | 4635G | TBD | | InternImage-H | Mask2Former | 896x896 | 62.5 / 62.9 | 1.31B | 4635G | TBD |
**模型推理速度** **模型推理速度**
......
README_EN.md
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...@@ -82,7 +82,7 @@ ADE20K, outperforming previous models by a large margin. ...@@ -82,7 +82,7 @@ ADE20K, outperforming previous models by a large margin.
<th>COCO</th><th>VOC 2007</th><th>VOC 2012</th><th>OpenImage</th><th>LVIS minival</th><th>LVIS val</th><th>BDD100K</th><th>nuScenes</th><th>CrowdHuman</th> <th>COCO</th><th>VOC 2007</th><th>VOC 2012</th><th>OpenImage</th><th>LVIS minival</th><th>LVIS val</th><th>BDD100K</th><th>nuScenes</th><th>CrowdHuman</th>
</tr> </tr>
<tr align="center"> <tr align="center">
<th>65.5</th><th>94.0</th><th>97.2</th><th>74.1</th><th>62.5</th><th>63.2</th><th>38.8</th><th>64.8</th><th>97.2</th> <th>65.5</th><th>94.0</th><th>97.2</th><th>74.1</th><th>65.8</th><th>63.2</th><th>38.8</th><th>64.8</th><th>97.2</th>
</tr> </tr>
</table> </table>
<br> <br>
...@@ -183,32 +183,38 @@ tasks ...@@ -183,32 +183,38 @@ tasks
**COCO Object Detection and Instance Segmentation** **COCO Object Detection and Instance Segmentation**
| backbone | method | schd | box mAP (val/test) | mask mAP (val/test) | #param | FLOPs | Download |
| backbone | method | schd | box mAP | mask mAP | #param | FLOPs | Download |
| :------------: | :----------------: | :---------: | :-----: | :------: | :-----: | :---: | :---: | | :------------: | :----------------: | :---------: | :-----: | :------: | :-----: | :---: | :---: |
| InternImage-T | Mask R-CNN | 1x | 47.2/- | 42.5/- | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_1x_coco.py) | | InternImage-T | Mask R-CNN | 1x | 47.2 | 42.5 | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_1x_coco.py) |
| InternImage-T | Mask R-CNN | 3x | 49.1/- | 43.7/- | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_3x_coco.py) | | InternImage-T | Mask R-CNN | 3x | 49.1 | 43.7 | 49M | 270G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_t_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_t_fpn_3x_coco.py) |
| InternImage-S | Mask R-CNN | 1x | 47.8/- | 43.3/- | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_1x_coco.py) | | InternImage-S | Mask R-CNN | 1x | 47.8 | 43.3 | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_1x_coco.py) |
| InternImage-S | Mask R-CNN | 3x | 49.7/- | 44.5/- | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_3x_coco.py) | | InternImage-S | Mask R-CNN | 3x | 49.7 | 44.5 | 69M | 340G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_s_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_s_fpn_3x_coco.py) |
| InternImage-B | Mask R-CNN | 1x | 48.8/- | 44.0/- | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_1x_coco.py) | | InternImage-B | Mask R-CNN | 1x | 48.8 | 44.0 | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_1x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_1x_coco.py) |
| InternImage-B | Mask R-CNN | 3x | 50.3/- | 44.8/- | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_3x_coco.py) | | InternImage-B | Mask R-CNN | 3x | 50.3 | 44.8 | 115M | 501G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/mask_rcnn_internimage_b_fpn_3x_coco.pth) \| [cfg](detection/configs/mask_rcnn/mask_rcnn_internimage_b_fpn_3x_coco.py) |
| InternImage-L | Cascade | 1x | 54.9/- | 47.7/- | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_1x_coco.py) | | InternImage-L | Cascade | 1x | 54.9 | 47.7 | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_1x_coco.py) |
| InternImage-L | Cascade | 3x | 56.1/- | 48.5/- | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_3x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_3x_coco.py) | | InternImage-L | Cascade | 3x | 56.1 | 48.5 | 277M | 1399G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_l_fpn_3x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_l_fpn_3x_coco.py) |
| InternImage-XL | Cascade | 1x | 55.3/- | 48.1/- | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_1x_coco.py) | | InternImage-XL | Cascade | 1x | 55.3 | 48.1 | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_1x_coco.py) |
| InternImage-XL | Cascade | 3x | 56.2/- | 48.8/- | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_3x_coco.py) | | InternImage-XL | Cascade | 3x | 56.2 | 48.8 | 387M | 1782G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/det_model/cascade_internimage_xl_fpn_1x_coco.pth) \| [cfg](detection/configs/cascade_mask_rcnn/cascade_internimage_xl_fpn_3x_coco.py) |
| InternImage-H | DINO (TTA) | 3x | 65.0/65.4 | -/- | 2.18B | TBD | TBD |
| InternImage-G | DINO (TTA) | 3x | 65.3/65.5 | -/- | 3B | TBD | TBD | | backbone | method | box mAP (val/test) | #param | FLOPs | Download |
| :------------: | :----------------: | :---------: | :------: | :-----: | :---: |
| InternImage-H | DINO (TTA) | 65.0 / 65.4 | 2.18B | TBD | TBD |
| InternImage-G | DINO (TTA) | 65.3 / 65.5 | 3B | TBD | TBD |
**ADE20K Semantic Segmentation** **ADE20K Semantic Segmentation**
| backbone | resolution | single scale | multi scale | #param | FLOPs | Download |
| :------------: | :--------: | :----------: | :---------: | :-----: | :---: | :---: | | backbone | method | resolution | mIoU (ss/ms) | #param | FLOPs | Download |
| InternImage-T | 512x512 | 47.9 | 48.1 | 59M | 944G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_t_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_t_512_160k_ade20k.py) | | :------------: | :--------: | :--------: | :----------: | :-----: | :---: | :---: |
| InternImage-S | 512x512 | 50.1 | 50.9 | 80M | 1017G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_s_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_s_512_160k_ade20k.py) | | InternImage-T | UperNet | 512x512 | 47.9 / 48.1 | 59M | 944G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_t_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_t_512_160k_ade20k.py) |
| InternImage-B | 512x512 | 50.8 | 51.3 | 128M | 1185G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_b_512_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_b_512_160k_ade20k.py) | | InternImage-S | UperNet | 512x512 | 50.1 / 50.9 | 80M | 1017G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_s_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_s_512_160k_ade20k.py) |
| InternImage-L | 640x640 | 53.9 | 54.1 | 256M | 2526G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_l_640_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_l_640_160k_ade20k.py) | | InternImage-B | UperNet | 512x512 | 50.8 / 51.3 | 128M | 1185G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_b_512_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_b_512_160k_ade20k.py) |
| InternImage-XL | 640x640 | 55.0 | 55.3 | 368M | 3142G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_xl_640_160k_ade20k.pth) \| [cfg](segmentation/configs/upernet/upernet_internimage_xl_640_160k_ade20k.py) | | InternImage-L | UperNet | 640x640 | 53.9 / 54.1 | 256M | 2526G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_l_640_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_l_640_160k_ade20k.py) |
| InternImage-H | 896x896 | 59.9 | 60.3 | 1.12B | 3566G | TBD | | InternImage-XL | UperNet | 640x640 | 55.0 / 55.3 | 368M | 3142G | [ckpt](https://github.com/OpenGVLab/InternImage/releases/download/seg_models/upernet_internimage_xl_640_160k_ade20k.pth) \| [cfg](segmentation/configs/ade20k/upernet_internimage_xl_640_160k_ade20k.py) |
| InternImage-H | 896x896 | 62.5 | 62.9 | 1.31B | 4635G | TBD | | InternImage-H | UperNet | 896x896 | 59.9 / 60.3 | 1.12B | 3566G | TBD |
| InternImage-H | Mask2Former | 896x896 | 62.5 / 62.9 | 1.31B | 4635G | TBD |
**Main Results of FPS** **Main Results of FPS**
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