mmdeploy

mirror of https://github.com/open-mmlab/mmdeploy.git synced 2025-01-14 08:09:43 +08:00

History

Li Zhang 682cb79bc5 [Enhancement] Optimize C++ demos (#1715 )

* optimize demos

* show text in image

* optimize demos

* fix minor

* fix minor

* fix minor

* install utils & fix demo file extensions

* rename

* parse empty flags

* antialias

* handle video complications

(cherry picked from commit 2b18596795b4028e175e0d80a5385efab317409f)

2023-02-07 21:12:44 +08:00

csharp

[Feature] Support feature map output for mmsegmentation (#1625 )

2023-02-07 21:04:20 +08:00

csrc

[Enhancement] Optimize C++ demos (#1715 )

2023-02-07 21:12:44 +08:00

java

Sync v0.7.0 to dev-1.x (#907 )

2022-08-19 09:30:13 +08:00

python

[Feature] Support feature map output for mmsegmentation (#1625 )

2023-02-07 21:04:20 +08:00

resources

update doc about codebase deployment (#1051 )

2022-09-24 18:05:24 +08:00

tutorials

[Enhancement]: add md link check github action (#1320 )

2022-12-08 16:13:51 +08:00

demo_rewrite.py

[Refactor] Refactor rewriter context for MMRazor (#1483 )

2022-12-13 19:03:56 +08:00

README.md

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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