Torchscript support (open-mmlab#159)

* support torchscript

* add nms

* add torchscript configs and update deploy process and dump-info

* typescript -> torchscript

* add torchscript custom extension support

* add ts custom ops again

* support mmseg unet

* [WIP] add optimizer for torchscript (open-mmlab#119)

* add passes

* add python api

* Torchscript optimizer python api (open-mmlab#121)

* add passes

* add python api

* use python api instead of executable

* Merge Master, update optimizer (open-mmlab#151)

* [Feature] add yolox ncnn (open-mmlab#29)

* add yolox ncnn

* add ncnn android performance of yolox

* add ut

* fix lint

* fix None bugs for ncnn

* test codecov

* test codecov

* add device

* fix yapf

* remove if-else for img shape

* use channelshuffle optimize

* change benchmark after channelshuffle

* fix yapf

* fix yapf

* fuse continuous reshape

* fix static shape deploy

* fix code

* drop pad

* only static shape

* fix static

* fix docstring

* Added mask overlay to output image, changed fprintf info messages to … (open-mmlab#55)

* Added mask overlay to output image, changed fprintf info messages to stdout

* Improved box filtering (filter area/score), make sure roi coordinates stay within bounds

* clang-format

* Support UNet in mmseg (open-mmlab#77)

* Repeatdataset in train has no CLASSES & PALETTE

* update result for unet

* update docstring for mmdet

* remove ppl for unet in docs

* fix ort wrap about input type (open-mmlab#81)

* Fix memleak (open-mmlab#86)

* delete []

* fix build error when enble MMDEPLOY_ACTIVE_LEVEL

* fix lint

* [Doc] Nano benchmark and tutorial (open-mmlab#71)

* add cls benchmark

* add nano zh-cn benchmark and en tutorial

* add device row

* add doc path to index.rst

* fix typo

* [Fix] fix missing deploy_core (open-mmlab#80)

* fix missing deploy_core

* mv flag to demo

* target link

* [Docs] Fix links in Chinese doc (open-mmlab#84)

* Fix docs in Chinese link

* Fix links

* Delete symbolic link and add links to html

* delete files

* Fix link

* [Feature] Add docker files (open-mmlab#67)

* add gpu and cpu dockerfile

* fix lint

* fix cpu docker and remove redundant

* use pip instead

* add build arg and readme

* fix grammar

* update readme

* add chinese doc for dockerfile and add docker build to build.md

* grammar

* refine dockerfiles

* add FAQs

* update Dpplcv_DIR for SDK building

* remove mmcls

* add sdk demos

* fix typo and lint

* update FAQs

* [Fix]fix check_env (open-mmlab#101)

* fix check_env

* update

* Replace convert_syncbatchnorm in mmseg (open-mmlab#93)

* replace convert_syncbatchnorm with revert_sync_batchnorm from mmcv

* change logger

* [Doc] Update FAQ for TensorRT (open-mmlab#96)

* update FAQ

* comment

* [Docs]: Update doc for openvino installation (open-mmlab#102)

* fix docs

* fix docs

* fix docs

* fix mmcv version

* fix docs

* rm blank line

* simplify non batch nms (open-mmlab#99)

* [Enhacement] Allow test.py to save evaluation results (open-mmlab#108)

* Add log file

* Delete debug code

* Rename logger

* resolve comments

* [Enhancement] Support mmocr v0.4+ (open-mmlab#115)

* support mmocr v0.4+

* 0.4.0 -> 0.4.1

* fix onnxruntime wrapper for gpu inference (open-mmlab#123)

* fix ncnn wrapper for ort-gpu

* resolve comment

* fix lint

* Fix typo (open-mmlab#132)

* lock mmcls version (open-mmlab#131)

* [Enhancement] upgrade isort in pre-commit config (open-mmlab#141)

* [Enhancement] upgrade isort in pre-commit config by refering to mmflow pr open-mmlab#87

* fix lint

* remove .isort.cfg and put its known_third_party to setup.cfg

* Fix ci for mmocr (open-mmlab#144)

* fix mmocr unittests

* remove useless

* lock mmdet maximum version to 2.20

* pip install -U numpy

* Fix capture_output (open-mmlab#125)

Co-authored-by: hanrui1sensetime <[email protected]>
Co-authored-by: Johannes L <[email protected]>
Co-authored-by: RunningLeon <[email protected]>
Co-authored-by: VVsssssk <[email protected]>
Co-authored-by: lvhan028 <[email protected]>
Co-authored-by: AllentDan <[email protected]>
Co-authored-by: Yifan Zhou <[email protected]>
Co-authored-by: 杨培文 (Yang Peiwen) <[email protected]>
Co-authored-by: Semyon Bevzyuk <[email protected]>

* configs for all tasks

* use torchvision roi align

* remote unnecessary code

* fix ut

* fix ut

* export

* det dynamic

* det dynamic

* add ut

* fix ut

* add ut and docs

* fix ut

* skip torchscript ut if no ops available

* add torchscript option to build.md

* update benchmark and resolve comments

* resolve conflicts

* rename configs

* fix mrcnn cuda test

* remove useless

* add version requirements to docs and comments to codes

* enable empty image exporting for torchscript and accelerate ORT inference for MRCNN

* rebase

* update example for torchscript.md

* update FAQs for torchscript.md

* resolve comments

* only use torchvision roi_align for torchscript

* fix ut

* use torchvision roi align when pool model is avg

* resolve comments

Co-authored-by: grimoire <[email protected]>
Co-authored-by: grimoire <[email protected]>
Co-authored-by: hanrui1sensetime <[email protected]>
Co-authored-by: Johannes L <[email protected]>
Co-authored-by: RunningLeon <[email protected]>
Co-authored-by: VVsssssk <[email protected]>
Co-authored-by: lvhan028 <[email protected]>
Co-authored-by: Yifan Zhou <[email protected]>
Co-authored-by: 杨培文 (Yang Peiwen) <[email protected]>
Co-authored-by: Semyon Bevzyuk <[email protected]>

Author: 11 people

mmdeploy/codebase/mmdet/models/roi_heads/single_level_roi_extractor.py

@@ -147,6 +147,11 @@ def single_roi_extractor__forward(ctx,
         device=target_lvls.device)
     target_lvls = torch.cat((_tmp, _tmp, target_lvls))
     for i in range(num_levels):
+        # use the roi align in torhcvision to accelerate the inference
+        # roi_align in MMCV is same as torchvision when pool mode is 'avg'
+        if backend == Backend.TORCHSCRIPT or self.roi_layers[
+                i].pool_mode == 'avg':
+            self.roi_layers[i].use_torchvision = True
         mask = target_lvls == i
         inds = mask.nonzero(as_tuple=False).squeeze(1)
         rois_t = rois[inds]