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Fast-SCNN implemented #58
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…o add_fast_scnn On sensetime servers, I modified the config files. On my PC, I modified collect_env.py. Now I'm going to merge these two modifications.
mmseg/models/backbones/fast_scnn.py
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class FeatureFusionModule(nn.Module): | ||
"""Feature fusion module.""" |
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We may use standard doc string here.
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Improved.
biburl = {https://dblp.org/rec/journals/corr/abs-1902-04502.bib}, | ||
bibsource = {dblp computer science bibliography, https://dblp.org} | ||
} | ||
``` |
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@article{poudel2019fast,
title={Fast-scnn: Fast semantic segmentation network},
author={Poudel, Rudra PK and Liwicki, Stephan and Cipolla, Roberto},
journal={arXiv preprint arXiv:1902.04502},
year={2019}
}
Can we merge now? |
There are conflicts with the master branch. |
…into open-mmlab-master # Conflicts: # docs/model_zoo.md # mmseg/models/backbones/__init__.py # tests/test_models/test_backbone.py
Now the master branch is correct. |
@@ -0,0 +1,40 @@ | |||
import pytest |
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Since InvertedResidual is moved to utils, the test case should also be moved accordingly.
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moved.
getting_started.md bug fixed.
This reverts commit dd0aadf
Can we merge now? |
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
Fast-SCNN implemented (open-mmlab#58)
* init commit: fast_scnn * 247917iters * 4x8_80k * configs placed in configs_unify. 4x8_80k exp.running. * mmseg/utils/collect_env.py modified to support Windows * study on lr * bug in configs_unify/***/cityscapes.py fixed. * lr0.08_100k * lr_power changed to 1.2 * log_config by_epoch set to False. * lr1.2 * doc strings added * add fast_scnn backbone test * 80k 0.08,0.12 * add 450k * fast_scnn test: fix BN bug. * Add different config files into configs/ * .gitignore recovered. * configs_unify del * .gitignore recovered. * delete sub-optimal config files of fast-scnn * Code style improved. * add docstrings to component modules of fast-scnn * relevant files modified according to Jerry's instructions * relevant files modified according to Jerry's instructions * lint problems fixed. * fast_scnn config extremely simplified. * InvertedResidual * fixed padding problems * add unit test for inverted_residual * add unit test for inverted_residual: debug 0 * add unit test for inverted_residual: debug 1 * add unit test for inverted_residual: debug 2 * add unit test for inverted_residual: debug 3 * add unit test for sep_fcn_head: debug 0 * add unit test for sep_fcn_head: debug 1 * add unit test for sep_fcn_head: debug 2 * add unit test for sep_fcn_head: debug 3 * add unit test for sep_fcn_head: debug 4 * add unit test for sep_fcn_head: debug 5 * FastSCNN type(dwchannels) changed to tuple. * t changed to expand_ratio. * Spaces fixed. * Update mmseg/models/backbones/fast_scnn.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Update mmseg/models/decode_heads/sep_fcn_head.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Update mmseg/models/decode_heads/sep_fcn_head.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Docstrings fixed. * Docstrings fixed. * Inverted Residual kept coherent with mmcl. * Inverted Residual kept coherent with mmcl. Debug 0 * _make_layer parameters renamed. * final commit * Arg scale_factor deleted. * Expand_ratio docstrings updated. * final commit * Readme for Fast-SCNN added. * model-zoo.md modified. * fast_scnn README updated. * Move InvertedResidual module into mmseg/utils. * test_inverted_residual module corrected. * test_inverted_residual.py moved. * encoder_decoder modified to avoid bugs when running PSPNet. getting_started.md bug fixed. * Revert "encoder_decoder modified to avoid bugs when running PSPNet. " This reverts commit dd0aadf Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
* init commit: fast_scnn * 247917iters * 4x8_80k * configs placed in configs_unify. 4x8_80k exp.running. * mmseg/utils/collect_env.py modified to support Windows * study on lr * bug in configs_unify/***/cityscapes.py fixed. * lr0.08_100k * lr_power changed to 1.2 * log_config by_epoch set to False. * lr1.2 * doc strings added * add fast_scnn backbone test * 80k 0.08,0.12 * add 450k * fast_scnn test: fix BN bug. * Add different config files into configs/ * .gitignore recovered. * configs_unify del * .gitignore recovered. * delete sub-optimal config files of fast-scnn * Code style improved. * add docstrings to component modules of fast-scnn * relevant files modified according to Jerry's instructions * relevant files modified according to Jerry's instructions * lint problems fixed. * fast_scnn config extremely simplified. * InvertedResidual * fixed padding problems * add unit test for inverted_residual * add unit test for inverted_residual: debug 0 * add unit test for inverted_residual: debug 1 * add unit test for inverted_residual: debug 2 * add unit test for inverted_residual: debug 3 * add unit test for sep_fcn_head: debug 0 * add unit test for sep_fcn_head: debug 1 * add unit test for sep_fcn_head: debug 2 * add unit test for sep_fcn_head: debug 3 * add unit test for sep_fcn_head: debug 4 * add unit test for sep_fcn_head: debug 5 * FastSCNN type(dwchannels) changed to tuple. * t changed to expand_ratio. * Spaces fixed. * Update mmseg/models/backbones/fast_scnn.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Update mmseg/models/decode_heads/sep_fcn_head.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Update mmseg/models/decode_heads/sep_fcn_head.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Docstrings fixed. * Docstrings fixed. * Inverted Residual kept coherent with mmcl. * Inverted Residual kept coherent with mmcl. Debug 0 * _make_layer parameters renamed. * final commit * Arg scale_factor deleted. * Expand_ratio docstrings updated. * final commit * Readme for Fast-SCNN added. * model-zoo.md modified. * fast_scnn README updated. * Move InvertedResidual module into mmseg/utils. * test_inverted_residual module corrected. * test_inverted_residual.py moved. * encoder_decoder modified to avoid bugs when running PSPNet. getting_started.md bug fixed. * Revert "encoder_decoder modified to avoid bugs when running PSPNet. " This reverts commit dd0aadf Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
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69.1% mIoU achieved, compared with 68% according to the original paper. Learning rate of 0.12 is suggested after multiple experimental trainings. However, three failures occurs when running pytest (failures are irrelevant with fast-scnn itself).