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* update doc about mmclassfication deployment * update install mmdeploy part * correct mmcls deployment commands * reformat supported models * add deployed model specification * update doc about mmdetection deployment * fix according to reviewer comments * fix according to reviewer comments * fix according to reviewer comments * fix according to reviewer comments * fix according to reviewer comments * fix according to reviewer comments * update doc about mmsegmentation deployment * update doc about mmocr deployment * check in cityscapes.png as an input image for converting mmsegmentation model * update mmocr deployment * update mmseg.md * update mmseg.md * update mmocr.md * update sdk model inference for mmocr deployment * update according to reviewer comments * update * update * update mmedit * update mmpose deployment * check in face.png for mmedit deployment * update * fix according to reviewer comments * remove duplicate doc * update docs in english * update codebase documents in chinese * fix according to reviewerss comments * update according reviewer comments * ObjectDetection -> Object Detection * InstanceSegmentation -> Instance Segmentation
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 |
---|---|
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