From 7bcfe674d157100a7ab62ed15864336ad2667532 Mon Sep 17 00:00:00 2001 From: mpelchat04 <38693210+mpelchat04@users.noreply.github.com> Date: Tue, 5 Mar 2024 09:23:34 -0500 Subject: [PATCH] Docs (#557) * update references in quickstart * add schema for GDL modes * update mode docs * update dataset --------- Co-authored-by: Turgeon-Pelchat --- docs/img/overview.png | Bin 0 -> 86246 bytes docs/source/dataset.rst | 39 ++++++++++++++++++--------- docs/source/mode.rst | 54 ++++++++++++++++++++++++++++++++----- docs/source/quickstart.rst | 17 +++++++----- 4 files changed, 84 insertions(+), 26 deletions(-) create mode 100644 docs/img/overview.png diff --git a/docs/img/overview.png b/docs/img/overview.png new file mode 100644 index 0000000000000000000000000000000000000000..4b406cf6511e4d1ce4529ce7fe3de8c741a9fbf5 GIT binary patch literal 86246 zcmce;g;!Ny)HO_ZcXxMpH%Ll%cXxMp3rLrAcS)y!bSR~C3aFHV-{$wc&lvCf4}1z9$3(+UV;a$Vt~~EAS?km#m(brmKyYuepac 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zzWd2V!kq0@7hbnZ_NBMtj&XByBN4s5@mn~`n4>bUNv)^}n}+WwAVr+qIMpZDNBwze vh}HVogoKlrc%hWXS}1Y68IMn_u9NT`?wr2y{1y2o{HLpFsB!0@edPZG*GF*z literal 0 HcmV?d00001 diff --git a/docs/source/dataset.rst b/docs/source/dataset.rst index b2b132e4..e5a5f746 100755 --- a/docs/source/dataset.rst +++ b/docs/source/dataset.rst @@ -3,11 +3,10 @@ Dataset +++++++ -The dataset configuration can be found :ref:`here `, this file contain -specific information about input data parameters for the execution of your command. The documentation -on the parameters use is explain in the :ref:`yaml ` section. +The dataset configuration defines the data (images, ground truth) and their parameters. The documentation +on the parameters used is explained in the :ref:`yaml ` section. -The sampling and inference steps requires a csv referencing input data. An example of input csv for +The tiling and inference steps requires a csv referencing input data. An example of input csv for massachusetts buildings dataset can be found in `tests `_. Each row of this csv is considered, in geo-deep-learning terms, to be an @@ -46,7 +45,22 @@ Dataset splits Split in csv should be either "trn", "tst" or "inference". The tiling script outputs lists of patches for "trn", "val" and "tst" and these lists are used as is during training. -Its proportion is set by the :ref:`tiling config `. +Its proportion is set by the :ref:`tiling config `. + +AOI +--- +An AOI is defined as an image (single imagery scene or mosaic), its content and metadata and the associated ground truth vector (optional). + +.. note:: + + AOI without ground truth vector can only be used for inference purposes. + + +The AOI's implementation in the code is as follow: + +.. autoclass:: dataset.aoi.AOI + :members: + :special-members: Raster and vector file compatibility ------------------------------------ @@ -66,15 +80,15 @@ Remote sensing is known to deal with raster files from a wide variety of formats To provide as much flexibility as possible with variable input formats for raster data, geo-deep-learning supports: -#. Multi-band raster files, to be used as is (all bands needed, all bands is expected order) -#. Multi-band raster files with more bands than needed (e.g. Actual is "BGRN", needed is "BGR") -#. Multi-band raster files with bands in different order than needed (e.g. Actual is "BGR", needed is "RGB") -#. Single-band raster files, identified with a common string pattern (see details below) -#. Single-band raster files, identified as assets in a stac item (see details below) +#. :ref:`Multi-band raster files, used as is ` (all bands needed, all bands is in the expected order) +#. :ref:`Multi-band raster files with more bands or different order than needed ` (e.g. Actual is "BGRN", needed is "BGR" OR Actual is "BGR", needed is "RGB") +#. :ref:`Single-band raster files, identified with a common string pattern ` (see details below) +#. :ref:`Single-band raster files, identified as assets in a stac item ` (see details below) To support these variable inputs, geo-deep-learning expects the first column of an input csv to be in the following formats. +.. _datasetmultiband: Multi-band raster files, used as is ==================================== @@ -87,7 +101,8 @@ This is the default and basic use. - ... * - my_dir/my_multiband_geofile.tif - ... - + +.. _datasetmultibandmorebands: Multi-band raster files with more bands or different order than needed ====================================================================== @@ -116,7 +131,7 @@ The ``bands`` parameter is set in the indexed from 1 (`docs `_). - +.. _datasetsingleband: Single-band raster files, identified with a common string pattern ================================================================= diff --git a/docs/source/mode.rst b/docs/source/mode.rst index 96bd2fe9..7fab5980 100755 --- a/docs/source/mode.rst +++ b/docs/source/mode.rst @@ -5,6 +5,11 @@ Mode The **mode** represent the assignment that you give to the code. +The following schema describes GDL's modes and concepts. + +.. image:: ../img/overview.png + :width: 600 + .. _datatiling: Data Tiling @@ -21,7 +26,7 @@ preparation phase creates `chips `_ +- ``mode`` (str) + 'min' or 'max', will minimize or maximize the chosen loss. +- ``max_used_ram`` (int, optional) + Used to calculate wether or not the process can use the GPU. If a GPU is already used by another process, the training can still be + pushed to this GPU if ``max_used_ram`` is not met. +- ``max_used_perc`` (int, optional) + Value between 0-100. Used to calculate wether or not the process can use the GPU. If a GPU is already used by another process, + the training can still be pushed to this GPU if ``max_used_perc`` is not met. +- ``state_dict_path`` (str, optional) + Path to a pretrained model (.pth.tar). +- ``state_dict_strict_load`` (bool, optional) + Defines whether to strictly enforce that the keys in state_dict match the keys returned by this Pytorch's state_dict() function. + Default: True. `Reference `_ +- ``compute_sampler_weights`` (bool, optional) + If provided, estimate sample weights by class for unbalanced datasets. + Uses `Sk-learn `_ + .. _inference: @@ -135,7 +175,7 @@ Inference The inference phase is the last one, it allows the use of a trained model to predict on new input data without ground truth. For this final step in the process, it need to assign every pixel in the original image a value corresponding to the most probable class with a certain level of confidence. Like the other two mode, the parameter -will be found in :ref:`configurationdefaultparam` under ``inference`` and this configuration file look a like +will be found in :ref:`configurationdefaultparam` under ``inference`` and this configuration file looks like (for binary inference): .. literalinclude:: ../../../config/inference/default_binary.yaml diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst index 5fd89624..649acb0c 100755 --- a/docs/source/quickstart.rst +++ b/docs/source/quickstart.rst @@ -21,7 +21,7 @@ Examples used here are for a bash shell in an Ubuntu GNU/Linux environment. Installation ------------ -Miniconda is suggested as the package manager for GDL. However, users are advised to `switch to libmamba ` as conda's default solver or to __directly use mamba__ instead of conda if they are facing extended installation time or other issues. Additional problems are grouped in the `troubleshooting section `. If issues persist, users are encouraged to open a new issue for assistance. +Miniconda is suggested as the package manager for GDL. However, users are advised to `switch to libmamba `_ as conda's default solver or to directly use mamba instead of conda if they are facing extended installation time or other issues. Additional problems are grouped in the :ref:`troubleshooting`. If issues persist, users are encouraged to open a new issue for assistance. Quickstart with conda @@ -37,21 +37,24 @@ python environment with the following commands: Tested on Ubuntu 20.04, Windows 10 and WSL 2. -Change conda's default solver for faster install (__Optional__) +Change conda's default solver for faster install (Optional) .. code-block:: console $ conda install -n base conda-libmamba-solver $ conda config --set solver libmamba -.. _troubleshooting - Troubleshooting ----------------- - .. code-block:: console - $ *ImportError: /lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.29' not found* +.. _troubleshooting: + +Troubleshooting +--------------- +Import error: .. code-block:: console + + $ *ImportError: /lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.29' not found* + $ $ # Export path to library or set it permenantly in your .bashrc file (example with conda) : $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/