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update model zoo
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Tau-J committed Sep 28, 2023
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Expand Up @@ -33,22 +33,69 @@ pip install -e .
- [x] Support WholeBody
- [x] Support ONNXRuntime backend
- [x] Support auto download and cache models
- [ ] Lightweight models
- [x] Lightweight models
- [ ] Support alias to choose model
- [ ] Support PoseTracker proposed in RTMPose
- [ ] Support TensorRT backend
- [x] Gradio interface
- [ ] Compatible with Controlnet
- [x] Compatible with Controlnet

## Model Zoo

Here are some models we have converted to onnx format.
By defaults, rtmlib will automatically download and apply models with the best performace. But you can also specify the model you want to use by passing the `onnx_model` argument.

More models can be found in [RTMPose Model Zoo](https://github.com/open-mmlab/mmpose/tree/dev-1.x/projects/rtmpose).

Here are some onnx models converted:

| Det | Pose |
| :-------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------: |
| [YOLOX-l](https://drive.google.com/file/d/1w9pXC8tT0p9ndMN-CArp1__b2GbzewWI/view?usp=sharing) | [RTMPose-m](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.zip) |
| | [RTMPose-m](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.zip) |

More models can be found in [RTMPose Model Zoo](https://github.com/open-mmlab/mmpose/tree/dev-1.x/projects/rtmpose).
### Detectors

<details open>
<summary><b>Person</b></summary>

Notes:
- Models trained on HumanArt can detect both real human and cartoon characters.
- Models trained on COCO can only detect real human.

| ONNX Model | Input Size | Description |
| :--------: | :--------: | :--------: |
| [YOLOX-l](https://drive.google.com/file/d/1w9pXC8tT0p9ndMN-CArp1__b2GbzewWI/view?usp=sharing) | 640x640 | trained on COCO val2017 |
| [YOLOX-nano](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_nano_8xb8-300e_humanart-40f6f0d0.zip) | 416x416 | trained on HumanArt |
| [YOLOX-tiny](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_tiny_8xb8-300e_humanart-6f3252f9.zip) | 416x416 | trained on HumanArt |
| [YOLOX-s](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_s_8xb8-300e_humanart-3ef259a7.zip) | 640x640 | trained on HumanArt |
| [YOLOX-m](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_m_8xb8-300e_humanart-c2c7a14a.zip) | 640x640 | trained on HumanArt |
| [YOLOX-l](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_l_8xb8-300e_humanart-ce1d7a62.zip) | 640x640 | trained on HumanArt |
| [YOLOX-x](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/yolox_x_8xb8-300e_humanart-a39d44ed.zip) | 640x640 | trained on HumanArt |

</details>

### Pose Estimators

<details open>
<summary><b>Body</b></summary>

| ONNX Model | Input Size | Description |
| :--------: | :--------: | :--------: |
| [RTMPose-t](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-t_simcc-body7_pt-body7_420e-256x192-026a1439_20230504.zip) | 256x192 | Body 17 Keypoints |
| [RTMPose-s](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-s_simcc-body7_pt-body7_420e-256x192-acd4a1ef_20230504.zip) | 256x192 | Body 17 Keypoints |
| [RTMPose-m](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.zip) | 256x192 | Body 17 Keypoints |
| [RTMPose-l](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-l_simcc-body7_pt-body7_420e-384x288-3f5a1437_20230504.zip) | 384x288 | Body 17 Keypoints |
| [RTMPose-x](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/onnx_sdk/rtmpose-x_simcc-body7_pt-body7_700e-384x288-71d7b7e9_20230629.zip) | 384x288 | Body 17 Keypoints |

</details>

<details open>
<summary><b>WholeBody</b></summary>

| ONNX Model | Input Size | Description |
| :--------: | :--------: | :--------: |
| [RTMW-x](https://download.openmmlab.com/mmpose/v1/projects/rtmw/onnx_sdk/rtmw-x_simcc-cocktail13_pt-ucoco_270e-384x288-0949e3a9_20230925.zip) | 384x288 | Wholebody 133 Keypoints |

</details>

## Demo

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