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source/arguments_edit/align.rst

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:align: center
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Animated gif comparing two separately processed, but aligned digital surface models.
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source/tutorials.rst

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Without any parameter tweaks, ODM chooses a good compromise between quality, speed and memory usage. If you want to get higher quality results, you need to tweak some parameters:
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* ``--orthophoto-resolution`` is the resolution of the orthophoto in cm/pixel. Decrease this value for a higher resolution result.
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* ``--ignore-gsd`` is a flag that instructs ODM to skip certain memory and speed optimizations that directly affect the orthophoto. Using this flag will increase runtime and memory usage, but may produce sharper results.
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* ``--texturing-data-term`` should be set to `area` in forest areas.
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* ``--mesh-size`` should be increased to ``300000-600000`` and ``--mesh-octree-depth`` should be increased to ``10-11`` in urban areas to recreate better buildings / roofs.
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::
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nohup python run.py myproject --split 1 --split-overlap 0 --ignore-gsd --depthmap-resolution 1000 --orthophoto-resolution 5 --dem-resolution 15 --pc-las --dsm
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nohup python run.py myproject --split 1 --split-overlap 0 --depthmap-resolution 1000 --orthophoto-resolution 5 --dem-resolution 15 --pc-las --dsm
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- This points ODM at the folder (in this example)
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``/mnt/odmdata/myproject/``. Provided the image_groups.txt and
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`Learn to edit <https://github.com/opendronemap/docs#how-to-make-your-first-contribution>`_ and help improve `this page <https://github.com/OpenDroneMap/docs/blob/publish/source/tutorials.rst>`_!
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Advanced
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Multi-temporal Datasets
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=======================
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When previously mapped sites need revisited, OpenDroneMap can align multiple versions of a dataset through time by using a prior point cloud or digital elevation model. As the prior point cloud `seems to provide better results <https://community.opendronemap.org/t/tips-to-increase-same-site-temporal-consistency/22161/7>`_, that is the approach we will review here.
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Workflow for multi-temporal datasets:
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=====================================
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#. Process your original data. This step doesn't require a ground control point file, but use one if absolute accuracy is a project requirement
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#. Download the Point Cloud from your first processed dataset as an LAZ file type (default). Rename the point cloud to align.laz
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[INFO] auto_boundary: True
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.. figure:: images/align_pc.gif
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:alt: Animated gif comparing two separately processed, but aligned digital surface models.
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:align: center
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Animated gif comparing two separately processed, but aligned digital surface models.
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********
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Advanced
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Using Singularity
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=================
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singularity run --bind /my/project:/datasets/code \
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--writable-tmpfs odm_latest.sif \
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--orthophoto-png --mesh-octree-depth 12 --ignore-gsd --dtm \
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--orthophoto-png --mesh-octree-depth 12 --dtm \
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--smrf-threshold 0.4 --smrf-window 24 --dsm --pc-csv --pc-las --orthophoto-kmz \
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--ignore-gsd --matcher-type flann --feature-quality ultra --max-concurrency 16 \
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--matcher-type flann --feature-quality ultra --max-concurrency 16 \
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--use-hybrid-bundle-adjustment --build-overviews --time --min-num-features 10000 \
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--project-path /datasets
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