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RunningLeon 787ebc2392
[Feature]: Support mmpose (#94) 
* add mmpose code

* update

* update

* add rewrites

* test trt

* test litehrnet with trt

* revert unused change

* add docs about mmpose

* add docstring and staticmethod

* update

* update

* update docs

* fix config name and docs

* add pose_detection ut

* add pose data

* fix lint of model.py

* add pose_detection_model ut

* fix docs and docstrinf

* add test_mmpose_models.py

* fix yapf

* fix lint

* fix create input

* support ort ut

* fix yapf

* fix docs

* fix createinput

* test ci bug

* rm test1.py

* fix yapf

* fix flake8

* fix yapf

* add config and update benchmark

* fix table format

* update mmpose benchmark

* update benchmark for mmpose

* run mmpose tests seperately in ci

* fix lint

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* add trt ut config

* fix test

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Co-authored-by: VVsssssk <shenkun@pjlab.org.cn>
Co-authored-by: hanrui1sensetime <hanrui1@sensetime.com>
 		2022-02-16 11:03:12 +08:00
..
csrc [Fix] fix missing deploy_core (#80) 2022-01-25 14:28:15 +08:00
resources [Feature]: Support mmpose (#94) 2022-02-16 11:03:12 +08:00
README.md
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demo_rewrite.py
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README.md

Demo

We provide a demo showing what our mmdeploy can do for general model deployment.

In demo_rewrite.py, a resnet18 model from torchvision is rewritten through mmdeploy tool. In our rewritten model, the forward function of resnet gets modified to only down sample the original input to 4x. Original onnx model of resnet18 and its rewritten are visualized through netron.

Prerequisite

Before we run demp_rewrite.py, we need to install pyppeteer through:

pip install pyppeteer

Demo results

The original resnet18 model and its modified one are visualized as follows. The left model is the original resnet18 while the right model is exported after rewritten.

Original resnet18 Rewritten model