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README.md
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......@@ -43,8 +43,8 @@ The official implementation of
## History
- [ ] Models/APIs for other downstream tasks
- [ ] Support [CVPR 2023 Workshop on End-to-End Autonomous Driving](https://opendrivelab.com/e2ead/cvpr23), see [here](https://github.com/OpenGVLab/InternImage/tree/master/autonomous_driving)
- [x] Models for other downstream tasks
- [x] Support [CVPR 2023 Workshop on End-to-End Autonomous Driving](https://opendrivelab.com/e2ead/cvpr23), see [here](https://github.com/OpenGVLab/InternImage/tree/master/autonomous_driving)
- [x] Support extracting intermediate features, see [here](classification/extract_feature.py)
- [x] Low-cost training with [DeepSpeed](https://github.com/microsoft/DeepSpeed), see [here](https://github.com/OpenGVLab/InternImage/tree/master/classification)
- [x] Compiling-free `.whl` package of DCNv3 operator, see [here](https://github.com/OpenGVLab/InternImage/releases/tag/whl_files)
......@@ -141,15 +141,15 @@ Some other projects related to InternImage include the pretraining algorithm "M3
<br>
<div>
| name | pretrain | resolution | acc@1 | #param | FLOPs | download |
| :------------: | :------------------: | :--------: | :---: | :----: | :---: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| InternImage-T | IN-1K | 224x224 | 83.5 | 30M | 5G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_t_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_t_1k_224) \| [cfg](configs/without_lr_decay/internimage_t_1k_224.yaml) |
| InternImage-S | IN-1K | 224x224 | 84.2 | 50M | 8G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_s_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_s_1k_224) \| [cfg](configs/without_lr_decay/internimage_s_1k_224.yaml) |
| InternImage-B | IN-1K | 224x224 | 84.9 | 97M | 16G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_b_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_b_1k_224) \| [cfg](configs/without_lr_decay/internimage_b_1k_224.yaml) |
| InternImage-L | IN-22K | 384x384 | 87.7 | 223M | 108G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_l_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_l_22kto1k_384) \| [cfg](configs/without_lr_decay/internimage_l_22kto1k_384.yaml) |
| InternImage-XL | IN-22K | 384x384 | 88.0 | 335M | 163G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_xl_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_xl_22kto1k_384) \| [cfg](configs/without_lr_decay/internimage_xl_22kto1k_384.yaml) |
| InternImage-H | Joint 427M -> IN-22K | 640x640 | 89.6 | 1.08B | 1478G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_h_22kto1k_640.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_h_22kto1k_640) \| [cfg](configs/without_lr_decay/internimage_h_22kto1k_640.yaml) |
| InternImage-G | Joint 427M -> IN-22K | 512x512 | 90.1 | 3B | 2700G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_g_22kto1k_512.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_g_22kto1k_512) \| [cfg](configs/without_lr_decay/internimage_g_22kto1k_512.yaml) |
| name | pretrain | resolution | acc@1 | #param | FLOPs | download |
| :------------: | :------------------: | :--------: | :---: | :----: | :---: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| InternImage-T | IN-1K | 224x224 | 83.5 | 30M | 5G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_t_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_t_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_t_1k_224.yaml) |
| InternImage-S | IN-1K | 224x224 | 84.2 | 50M | 8G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_s_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_s_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_s_1k_224.yaml) |
| InternImage-B | IN-1K | 224x224 | 84.9 | 97M | 16G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_b_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_b_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_b_1k_224.yaml) |
| InternImage-L | IN-22K | 384x384 | 87.7 | 223M | 108G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_l_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_l_22kto1k_384) \| [cfg](classification/configs/without_lr_decay/internimage_l_22kto1k_384.yaml) |
| InternImage-XL | IN-22K | 384x384 | 88.0 | 335M | 163G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_xl_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_xl_22kto1k_384) \| [cfg](classification/configs/without_lr_decay/internimage_xl_22kto1k_384.yaml) |
| InternImage-H | Joint 427M -> IN-22K | 640x640 | 89.6 | 1.08B | 1478G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_h_22kto1k_640.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_h_22kto1k_640) \| [cfg](classification/configs/without_lr_decay/internimage_h_22kto1k_640.yaml) |
| InternImage-G | Joint 427M -> IN-22K | 512x512 | 90.1 | 3B | 2700G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_g_22kto1k_512.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_g_22kto1k_512) \| [cfg](classification/configs/without_lr_decay/internimage_g_22kto1k_512.yaml) |
</div>
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README_CN.md
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......@@ -42,8 +42,8 @@
## 项目功能
- [ ] 各类下游任务
- [ ] 支持 [CVPR 2023 Workshop on End-to-End Autonomous Driving](https://opendrivelab.com/e2ead/cvpr23)，[详见](https://github.com/OpenGVLab/InternImage/tree/master/autonomous_driving)
- [x] 各类下游任务
- [x] 支持 [CVPR 2023 Workshop on End-to-End Autonomous Driving](https://opendrivelab.com/e2ead/cvpr23)，[详见](https://github.com/OpenGVLab/InternImage/tree/master/autonomous_driving)
- [x] 支持提取模型中间层特征，[详见](classification/extract_feature.py)
- [x] 支持基于 [DeepSpeed](https://github.com/microsoft/DeepSpeed) 的低成本训练，[详见](https://github.com/OpenGVLab/InternImage/tree/master/classification)
- [x] DCNv3 算子预编译 `.whl` 包，[详见](https://github.com/OpenGVLab/InternImage/releases/tag/whl_files)
......@@ -140,15 +140,15 @@ InternImage 是一个由上海人工智能实验室、清华大学等机构的
<br>
<div>
| name | pretrain | resolution | acc@1 | #param | FLOPs | download |
| :------------: | :----------: | :--------: | :---: | :----: | :---: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| InternImage-T | ImageNet-1K | 224x224 | 83.5 | 30M | 5G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_t_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_t_1k_224) \| [cfg](configs/without_lr_decay/internimage_t_1k_224.yaml) |
| InternImage-S | ImageNet-1K | 224x224 | 84.2 | 50M | 8G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_s_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_s_1k_224) \| [cfg](configs/without_lr_decay/internimage_s_1k_224.yaml) |
| InternImage-B | ImageNet-1K | 224x224 | 84.9 | 97M | 16G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_b_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_b_1k_224) \| [cfg](configs/without_lr_decay/internimage_b_1k_224.yaml) |
| InternImage-L | ImageNet-22K | 384x384 | 87.7 | 223M | 108G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_l_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_l_22kto1k_384) \| [cfg](configs/without_lr_decay/internimage_l_22kto1k_384.yaml) |
| InternImage-XL | ImageNet-22K | 384x384 | 88.0 | 335M | 163G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_xl_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_xl_22kto1k_384) \| [cfg](configs/without_lr_decay/internimage_xl_22kto1k_384.yaml) |
| InternImage-H | Joint 427M | 640x640 | 89.6 | 1.08B | 1478G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_h_22kto1k_640.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_h_22kto1k_640) \| [cfg](configs/without_lr_decay/internimage_h_22kto1k_640.yaml) |
| InternImage-G | Joint 427M | 512x512 | 90.1 | 3B | 2700G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_g_22kto1k_512.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_g_22kto1k_512) \| [cfg](configs/without_lr_decay/internimage_g_22kto1k_512.yaml) |
| name | pretrain | resolution | acc@1 | #param | FLOPs | download |
| :------------: | :----------: | :--------: | :---: | :----: | :---: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| InternImage-T | ImageNet-1K | 224x224 | 83.5 | 30M | 5G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_t_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_t_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_t_1k_224.yaml) |
| InternImage-S | ImageNet-1K | 224x224 | 84.2 | 50M | 8G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_s_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_s_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_s_1k_224.yaml) |
| InternImage-B | ImageNet-1K | 224x224 | 84.9 | 97M | 16G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_b_1k_224.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_b_1k_224) \| [cfg](classification/configs/without_lr_decay/internimage_b_1k_224.yaml) |
| InternImage-L | ImageNet-22K | 384x384 | 87.7 | 223M | 108G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_l_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_l_22kto1k_384) \| [cfg](classification/configs/without_lr_decay/internimage_l_22kto1k_384.yaml) |
| InternImage-XL | ImageNet-22K | 384x384 | 88.0 | 335M | 163G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_xl_22kto1k_384.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_xl_22kto1k_384) \| [cfg](classification/configs/without_lr_decay/internimage_xl_22kto1k_384.yaml) |
| InternImage-H | Joint 427M | 640x640 | 89.6 | 1.08B | 1478G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_h_22kto1k_640.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_h_22kto1k_640) \| [cfg](classification/configs/without_lr_decay/internimage_h_22kto1k_640.yaml) |
| InternImage-G | Joint 427M | 512x512 | 90.1 | 3B | 2700G | [pth](https://huggingface.co/OpenGVLab/InternImage/resolve/main/internimage_g_22kto1k_512.pth) \| [hf](https://huggingface.co/OpenGVLab/internimage_g_22kto1k_512) \| [cfg](classification/configs/without_lr_decay/internimage_g_22kto1k_512.yaml) |
</div>
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classification/README.md
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......@@ -80,7 +80,6 @@ We provide the following ways to prepare data:
<details open>
<summary>Standard ImageNet-1K</summary>
<br>
- We use standard ImageNet dataset, you can download it from http://image-net.org/.
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detection/README.md
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......@@ -114,10 +114,10 @@ Prepare datasets according to the guidelines in [MMDetection v2.28.1](https://gi
| DINO | InternImage-L | 1x | 57.6 | 241M | [config](./configs/coco/dino_4scale_internimage_l_1x_coco_0.1x_backbone_lr.py) | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_internimage_l_1x_coco_0.1x_backbone_lr.pth) \| [log](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_internimage_l_1x_coco_0.1x_backbone_lr.log.json) |
| DINO | InternImage-H | 1x | 63.4 | 1.1B | [config](./configs/coco/dino_4scale_internimage_h_objects365_coco_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_internimage_h_objects365_coco.pth) |
| DINO | CB-InternImage-H | 1x | 64.5 | 2.2B | [config](./configs/coco/dino_4scale_cbinternimage_h_objects365_coco_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_cbinternimage_h_objects365_coco.pth) |
| DINO (TTA) | CB-InternImage-H | 1x | 65.0 | 2.2B | TODO | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_cbinternimage_h_objects365_coco.pth) |
| DINO (TTA) | CB-InternImage-H | 1x | 65.0 | 2.2B | - | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_cbinternimage_h_objects365_coco.pth) |
| DINO | InternImage-G | 1x | 64.2 | 3.1B | [config](./configs/coco/dino_4scale_internimage_g_objects365_coco_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/InternImage/resolve/main/dino_4scale_internimage_g_objects365_coco.pth) |
| DINO (TTA) | CB-InternImage-G | 1x | 65.1 | 6B | TODO | TODO |
| DINO (TTA) | CB-InternImage-G | 1x | 65.3 | 6B | TODO | TODO |
| DINO | CB-InternImage-G | 1x | 65.1 | 6B | - | - |
| DINO (TTA) | CB-InternImage-G | 1x | 65.3 | 6B | - | - |
</div>
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