[Feature] Support Real-time model ERFNet #960
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Inference metric has done. Input Original repo is My MMSeg repo is also |
Codecov Report
@@ Coverage Diff @@
## master #960 +/- ##
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+ Coverage 89.57% 89.74% +0.16%
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Files 120 121 +1
Lines 6717 6828 +111
Branches 1122 1139 +17
==========================================
+ Hits 6017 6128 +111
Misses 496 496
Partials 204 204
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Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
Junjun2016
reviewed
Oct 16, 2021
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Hi @MengzhangLI |
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Refactoring the code has been done.
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The training metric has been done.
Result of scratch ERFNet with FCN head using MMSegmentation is 70.8.
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xvjiarui
reviewed
Oct 27, 2021
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Please fix the conflict. |
Junjun2016
reviewed
Nov 8, 2021
Junjun2016
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Nov 8, 2021
Junjun2016
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Junjun2016
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Nov 8, 2021
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Not correct, should update in the future.<html>
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Re: [open-mmlab/mmsegmentation] [Feature] Support Real-time model ERFNet (#960)
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***@***.***</b> commented on this pull request.</p>
<hr>
<p>In <a href="#960 (comment)">configs/_base_/models/fcn_erfnet.py</a>:</p>
<pre style='color:#555'>> @@ -0,0 +1,32 @@
+# model settings
</pre>
<p dir="auto">I just followed name of <a href="https://github.com/open-mmlab/mmsegmentation/tree/master/configs/unet">UNet</a> which put decoder head (fcn, pspnet and deeplabv3) in front of backbone (unet). Altogether with <code>configs/_base_/models/fcn_unet_s5-d16.py</code>.</p>
<p style="font-size:small;-webkit-text-size-adjust:none;color:#666;">—<br />You are receiving this because you commented.<br />Reply to this email directly, <a href="#960 (comment)">view it on GitHub</a>, or <a href="https://github.com/notifications/unsubscribe-auth/AD7REKOSUEIHJAVAPURWQNDULDJ2BANCNFSM5F5TC7KQ">unsubscribe</a>.<br />Triage notifications on the go with GitHub Mobile for <a href="https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675">iOS</a> or <a href="https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub">Android</a>.
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Generally, the first name should be the algorithm's name.<html>
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2021年11月09日 16:13
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Re: [open-mmlab/mmsegmentation] [Feature] Support Real-time model ERFNet (#960)
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***@***.***</b> commented on this pull request.</p>
<hr>
<p>In <a href="#960 (comment)">configs/_base_/models/fcn_erfnet.py</a>:</p>
<pre style='color:#555'>> @@ -0,0 +1,32 @@
+# model settings
</pre>
<p dir="auto">I just followed name of <a href="https://github.com/open-mmlab/mmsegmentation/tree/master/configs/unet">UNet</a> which put decoder head (fcn, pspnet and deeplabv3) in front of backbone (unet). Altogether with <code>configs/_base_/models/fcn_unet_s5-d16.py</code>.</p>
<p style="font-size:small;-webkit-text-size-adjust:none;color:#666;">—<br />You are receiving this because you commented.<br />Reply to this email directly, <a href="#960 (comment)">view it on GitHub</a>, or <a href="https://github.com/notifications/unsubscribe-auth/AD7REKOSUEIHJAVAPURWQNDULDJ2BANCNFSM5F5TC7KQ">unsubscribe</a>.<br />Triage notifications on the go with GitHub Mobile for <a href="https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675">iOS</a> or <a href="https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub">Android</a>.
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Hi @MengzhangLI |
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Please merge the master branch into your branch, thank you. |
MengzhangLI
commented
Nov 26, 2021
Junjun2016
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Nov 30, 2021
Junjun2016
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Junjun2016
reviewed
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Junjun2016
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Nov 30, 2021
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Please fix the lint |
xvjiarui
approved these changes
Dec 2, 2021
bowenroom
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Feb 25, 2022
* first commit * Fixing Unittest Error * first refactory of ERFNet * Refactorying NonBottleneck1d Module * uploading models&logs * uploading models&logs * fix partial bugs & typos * ERFNet * add ERFNet with FCNHead * fix typos of ERFNet * add name on README.md cover * chane name to T-ITS'2017 * fix lint error
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ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation
Paper: http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17tits.pdf (Current Citation: 596)
Repo: https://github.com/Eromera/erfnet_pytorch (Current Star: 346)
Validation Result 72.20 %
These two figures below may be helpful for code review.
Structure of the model:
Two main block of the structure (Downsampler Block and non-bt-1D):
