Use python to generate orthophotos, digital elevation models and 3D modeling of drone images

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[OpenDroneMap] is an open source aerial [image processing] tool that can process aerial images for point clouds, orthophotos, and elevation models, as well as 3D reconstruction to generate 3D models. It is an artifact, and the effect is similar to that of pix4d and other software (I currently only generate the orthographic image of the drone image).
  According to the official documentation, PyODM can easily create orthomaps, DEMs, 3d models and [point clouds] of drone images .
  The effect of the ortho map is as follows:
  Let’s start using OpenDroneMap’s python library PyODM .
  Note: If there is exif information in the picture, odm can directly generate the orthophoto of tif. To add exif information to pictures, please refer to the following blog.

1. Environmental preparation

Install the pyodm package

Just install it with pip.

pip install -U pyodm

start docker

pyodm needs to start docker, so you need to install docker before using it. I
will not talk about the installation of windows. You can Baidu by yourself. The following describes the installation of docker under the linux system.

#Install docker 
$ curl -fsSL | sudo apt-key add - 
$ sudo apt-get install -y docker-ce 

#Start docker, here will download what you need package, so it takes a while. 
$ sudo docker run -ti -p 3000:3000 opendronemap/nodeodm

2. python tutorial

The general process is like this, first connect to Node, then create a new task, then wait for the task execution to complete, and finally get the result.
  The key here is that there is an option option when creating a new task, which can set some configurations. According to the [documentation] , the configuration will affect the processing speed and the quality of the results.
  For the production of orthophotos, some parameters that need to be configured (parameters can be viewed in the [official documentation] ) are as follows:

  • orthophoto-resolution: m/pixel, indicating ground resolution
  • dsm: whether to generate dsm, if not, select false to speed up processing
  • ignore-gsd: Set to True to skip some accelerated processing, and the resulting image quality will be better
  • min-num-features: the number of feature points to find, the more the number, the better the quality and the longer the processing time
  • texturing-nadir-weight: Official recommendation, set to 29-32 in the city, 0-6 for grass or flat bottom
  • mesh-octree-depth: The official recommendation is to set it to 10-11 to increase the smoothness of the building roof.

Note: When making an orthophoto, it is best to select a picture with data of at least two tracks. The data splicing of one route will fail, that is, task.wait_for_completion() will return failed.

import os
from pyodm import Node
import time
from tqdm import tqdm

image_dir = 'testdata/' 
result_path = image_dir.split( '/' )[ 0 ]+ '_results' 
ip = 'xxx.xx.xx.xx'  # Change to your own ip 
port = 3000

start = time.time()
images_name = os.listdir(image_dir)
images_name = [image_dir+image_name for image_name in images_name]

n = Node(ip, port)
print( "Node connection is successful, {} images start processing" .format(len(images_name)))

task = n.create_task(images_name, {'orthophoto-resolution': 0.0274,"min-num-features":35000})
print( "Task creation completed" )
pbar = tqdm(total=100)
processing = 0
while True:
    info =
    if info.progress==100:
    processing = info.progress
    if info.last_error!='':
        print("error ", info.last_error)


print( "processing completed" )
 # task.wait_for_completion()

print( "{} images consume {} seconds" .format(len(images_name), time.time() - start))

3. Other

Viewing official documents may require scientific Internet access, so the options are listed.

-h, --help            show this help message and exit
--images <path>, -i <path>
                      Path to input images
--project-path <path>
                      Path to the project folder
--resize-to <integer>
                      resizes images by the largest side for opensfm. Set to
                      -1 to disable.
                                              Default: 2048
--end-with <string>, -e <string>
                      Can be one of:dataset | split | merge | opensfm | mve
                      | odm_filterpoints | odm_meshing | mvs_texturing |
                      odm_georeferencing | odm_dem | odm_orthophoto
--rerun <string>, -r <string>
                      Can be one of:dataset | split | merge | opensfm | mve
                      | odm_filterpoints | odm_meshing | mvs_texturing |
                      odm_georeferencing | odm_dem | odm_orthophoto
--rerun-all           force rerun of all tasks
--rerun-from <string>
                      Can be one of:dataset | split | merge | opensfm | mve
                      | odm_filterpoints | odm_meshing | mvs_texturing |
                      odm_georeferencing | odm_dem | odm_orthophoto
--proj <PROJ4 string>
                      Projection used to transform the model into geographic
--min-num-features <integer>
                      Minimum number of features to extract per image. More
                      features leads to better results but slower execution.
                      Default: 8000
--matcher-neighbors <integer>
                      Number of nearest images to pre-match based on GPS
                      exif data. Set to 0 to skip pre-matching. Neighbors
                      works together with Distance parameter, set both to 0
                      to not use pre-matching. OpenSFM uses both parameters
                      at the same time, Bundler uses only one which has
                      value, prefering the Neighbors parameter.
                                              Default: 8
--matcher-distance <integer>
                      Distance threshold in meters to find pre-matching
                      images based on GPS exif data. Set both matcher-
                      neighbors and this to 0 to skip pre-matching.
                                              Default: 0
                      Turn off camera parameter optimization during bundler
                                              Off by default unless --camera parameter used
--camera-lens <string>
                      Can be one of auto | perspective | brown | fisheye | spherical
                      Set a camera projection type. Manually setting a value
                      can help improve geometric undistortion. By default the application
                      tries to determine a lens type from the images metadata.
                                              Default: auto
--max-concurrency <positive integer>
                      The maximum number of processes to use in various
                      processes. Peak memory requirement is ~1GB per thread
                      and 2 megapixel image resolution.
                                              Default: number of cores
--depthmap-resolution <positive float>
                      Controls the density of the point cloud by setting the
                      resolution of the depthmap images. Higher values take
                      longer to compute and more memory but produce denser
                                              point clouds.
                      Default: 640
--opensfm-depthmap-min-consistent-views <integer: 2 <= x <= 9>
                      Minimum number of views that should reconstruct a
                      point for it to be valid. Use lower values if your
                      images have less overlap. Lower values result in
                      denser point clouds but with more noise. Only applies
                                              if using OpenSfM for dense matching.
                                              Default: 3
--opensfm-depthmap-method <string>
                      Raw depthmap computation algorithm. PATCH_MATCH and
                      PATCH_MATCH_SAMPLE are faster, but might miss some
                      valid points. BRUTE_FORCE takes longer but produces
                      denser reconstructions.
                                              Default: PATCH_MATCH
--opensfm-depthmap-min-patch-sd <positive float>
                      When using PATCH_MATCH or PATCH_MATCH_SAMPLE, controls
                      the standard deviation threshold to include patches.
                      Patches with lower standard deviation are ignored.
                      Default: 1
                      Run local bundle adjustment for every image added to
                      the reconstruction and a global adjustment every 100
                      images. Speeds up reconstruction for very large
--mve-confidence <float: 0 <= x <= 1>
                      Discard points that have less than a certain
                      confidence threshold. This only affects dense
                      reconstructions performed with MVE. Higher values
                      discard more points.
                                              Default: 0.6
--use-3dmesh          Use a full 3D mesh to compute the orthophoto instead
                      of a 2.5D mesh. This option is a bit faster and
                      provides similar results in planar areas.
--skip-3dmodel        Skip generation of a full 3D model. This can save time
                      if you only need 2D results such as orthophotos and
--use-opensfm-dense   Use opensfm to compute dense point cloud alternatively
--ignore-gsd          Ignore Ground Sampling Distance (GSD). GSD caps the
                      maximum resolution of image outputs and resizes images
                      when necessary, resulting in faster processing and
                      lower memory usage. Since GSD is an estimate,
                      sometimes ignoring it can result in slightly better
                      image output quality.
--mesh-size <positive integer>
                      The maximum vertex count of the output mesh.
                                              Default: 100000
--mesh-octree-depth <positive integer>
                      Oct-tree depth used in the mesh reconstruction,
                      increase to get more vertices, recommended values are
                                              Default: 9
--mesh-samples <float >= 1.0>
                      Number of points per octree node, recommended and
                      Default: 1.0
--mesh-point-weight <positive float>
                      This floating point value specifies the importance
                      that interpolation of the point samples is given in
                      the formulation of the screened Poisson equation. The
                      results of the original (unscreened) Poisson
                      Reconstruction can be obtained by setting this value
                      to 0.
                                              Default: 4
--fast-orthophoto     Skips dense reconstruction and 3D model generation. It
                      generates an orthophoto directly from the sparse
                      reconstruction. If you just need an orthophoto and do
                      not need a full 3D model, turn on this option.
--crop <positive float>
                      Automatically crop image outputs by creating a smooth
                      buffer around the dataset boundaries, shrinked by N
                      meters. Use 0 to disable cropping.
                                              Default: 3
--pc-classify         Classify the point cloud outputs using a Simple
                      Morphological Filter. You can control the behavior of
                      this option by tweaking the --dem-* parameters.
                      Default: False
--pc-csv              Export the georeferenced point cloud in CSV format.
                      Default: False
--pc-las              Export the georeferenced point cloud in LAS format.
                      Default: False
--pc-filter <positive float>
                      Filters the point cloud by removing points that
                      deviate more than N standard deviations from the local
                      mean. Set to 0 to disable filtering.
                                              Default: 2.5
--smrf-scalar <positive float>
                      Simple Morphological Filter elevation scalar
                                              Default: 1.25
--smrf-slope <positive float>
                      Simple Morphological Filter slope parameter (rise over
                                              Default: 0.15
--smrf-threshold <positive float>
                      Simple Morphological Filter elevation threshold
                      parameter (meters).
                                              Default: 0.5
--smrf-window <positive float>
                      Simple Morphological Filter window radius parameter
                                              Default: 18.0
--texturing-data-term <string>
                      Data term: [area, gmi].
                                              Default: gmi
--texturing-nadir-weight <integer: 0 <= x <= 32>
                      Affects orthophotos only. Higher values result in
                      sharper corners, but can affect color distribution and
                      blurriness. Use lower values for planar areas and
                      higher values for urban areas. The default value works
                      well for most scenarios.
                                              Default: 16
--texturing-outlier-removal-type <string>
                      Type of photometric outlier removal method: [none,
                      gauss_damping, gauss_clamping].
                                              Default: gauss_clamping
                      Skip geometric visibility test.
                                              Default: False
                      Skip global seam leveling. Useful for IR data.
                                              Default: False
                      Skip local seam blending.
                                              Default: False
                      Skip filling of holes in the mesh.
                                              Default: False
                      Keep faces in the mesh that are not seen in any
                                              Default: False
--texturing-tone-mapping <string>
                      Turn on gamma tone mapping or none for no tone
                      mapping. Choices are 'gamma' or 'none'.
                                              Default: none
--gcp <path string>   path to the file containing the ground control points
                      used for georeferencing. Default: None. The file needs
                      to be on the following line format: easting northing
                      height pixelrow pixelcol imagename
--use-exif            Use this tag if you have a gcp_list.txt but want to
                      use the exif geotags instead
--dtm                 Use this tag to build a DTM (Digital Terrain Model,
                      ground only) using a simple morphological filter.
                      Check the --dem* and --smrf* parameters for finer
--dsm                 Use this tag to build a DSM (Digital Surface Model,
                      ground + objects) using a progressive morphological
                      filter. Check the --dem* parameters for finer tuning.
--dem-gapfill-steps <positive integer>
                      Number of steps used to fill areas with gaps. Set to 0
                      to disable gap filling. Starting with a radius equal
                      to the output resolution, N different DEMs are
                      generated with progressively bigger radius using the
                      inverse distance weighted (IDW) algorithm and merged
                      together. Remaining gaps are then merged using nearest
                      neighbor interpolation.
                                              Default: 3
--dem-resolution <float>
                      DSM/DTM resolution in cm / pixel.
                                              Default: 5
--dem-decimation <positive integer>
                      Decimate the points before generating the DEM. 1 is no
                      decimation (full quality). 100 decimates ~99% of the
                      points. Useful for speeding up generation.
                                              Default: 1
--dem-euclidean-map   Computes an euclidean raster map for each DEM. The map
                      reports the distance from each cell to the nearest
                      NODATA value (before any hole filling takes place).
                      This can be useful to isolate the areas that have been
                                              Default: False
--orthophoto-resolution <float > 0.0>
                      Orthophoto resolution in cm / pixel.
                                              Default: 5
                      Set this parameter if you want a stripped geoTIFF.
                      Default: False
--orthophoto-compression <string>
                      Set the compression to use. Note that this could break
                      gdal_translate if you don't know what you are doing.
                      Options: JPEG, LZW, PACKBITS, DEFLATE, LZMA, NONE.
                      Default: DEFLATE
--orthophoto-bigtiff {YES,NO,IF_NEEDED,IF_SAFER}
                      Control whether the created orthophoto is a BigTIFF or
                      classic TIFF. BigTIFF is a variant for files larger
                      than 4GiB of data. Options are YES, NO, IF_NEEDED,
                      IF_SAFER. See GDAL specs:
             for more info.
                      Default: IF_SAFER
--orthophoto-cutline  Generates a polygon around the cropping area that cuts
                      the orthophoto around the edges of features. This
                      polygon can be useful for stitching seamless mosaics
                      with multiple overlapping orthophotos.
                                              Default: False
--build-overviews     Build orthophoto overviews using gdaladdo.
--verbose, -v         Print additional messages to the console
                                              Default: False
--time                Generates a benchmark file with runtime info
                                              Default: False
--version             Displays version number and exits.
--split <positive integer>
                      Average number of images per submodel. When splitting
                      a large dataset into smaller submodels, images are
                      grouped into clusters. This value regulates the number
                      of images that each cluster should have on average.
--split-overlap <positive integer>
                      Radius of the overlap between submodels. After
                      grouping images into clusters, images that are closer
                      than this radius to a cluster are added to the
                      cluster. This is done to ensure that neighboring
                      submodels overlap.
--sm-cluster <string>
                      URL to a ClusterODM instance for distributing a
                      split-merge workflow on multiple nodes in parallel.
                      Default: None
--merge <string>      Choose what to merge in the merge step in a split
                      dataset. By default all available outputs are merged.
                      Default: all

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