AutoLay
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manila95
A novel benchmark dataset for Monocular Layout prediction
Bumps [pillow](https://github.com/python-pillow/Pillow) from 6.2.0 to 9.3.0. Release notes Sourced from pillow's releases. 9.3.0 https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html Changes Initialize libtiff buffer when saving #6699 [@radarhere] Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [@wiredfool]...
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Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 0.12.0 to 2.9.3. Release notes Sourced from tensorflow's releases. TensorFlow 2.9.3 Release 2.9.3 This release introduces several vulnerability fixes: Fixes an overflow in tf.keras.losses.poisson (CVE-2022-41887) Fixes a...
Bumps [protobuf](https://github.com/protocolbuffers/protobuf) from 3.10.0 to 3.18.3. Release notes Sourced from protobuf's releases. Protocol Buffers v3.18.3 C++ Reduce memory consumption of MessageSet parsing This release addresses a Security Advisory for C++...
> https://github.com/hbutsuak95/monolayout/issues/28
Hello. Firstly I'd like to thank you for sharing your work with dataset. But it seems that released data is not complete: there is an instruction how to get raw...
Bumps [opencv-python](https://github.com/skvark/opencv-python) from 4.1.1.26 to 4.2.0.32. Release notes Sourced from opencv-python's releases. 4.2.0.32 opencv-python: https://pypi.org/project/opencv-python/ opencv-contrib-python: https://pypi.org/project/opencv-contrib-python/ opencv-python-headless: https://pypi.org/project/opencv-python-headless/ opencv-contrib-python-headless: https://pypi.org/project/opencv-contrib-python-headless/ OpenCV version 4.2.0. Changes: macOS environment updated from xcode8.3...
Hi, maybe forgot to upload “eval.py”, run “python train.py” Traceback (most recent call last): File "train.py", line 19, in from eval import evaluate_layout ModuleNotFoundError: No module named 'eval'
Hi, thanks a lot for sharing your interesting and great work. We downloaded the dataset at https://autolay.github.io/index.html and there are some problems. > 1. We don't seem to find the...
In my understanding, the layout for each class needs a specific decoder, right? So it is a binary classification problem for each class?
Hi, thanks a lot for giving an explicit definition of Amodal layout estimation for autonomous driving. It's an interesting and practical task. I'd like to learn more about this task....