Generating Photogrammetry Products

This page aims to guide a user through photogrammetry processing using Agisoft PhotoScan.
Refer to ~arsf/doc/photoscan_processing/ for a step by step guide using a PhotoScan GUI.

Processing using PhotoScan

Overview: The following files comprise the arf_photoscan library:

arf_photoscan/
	init.py
	ps_export.py
	ps_processing.py
	ps_tools.py
	ps_tools.pyc
ps_ortho_processing_after_input_gcp.py
ps_ortho_processing_before_input_gcp.py
README.md
templates/
	ps_workflow.cfg

The arf_photoscan library currently contains two scripts for automating PhotoScan processing of NERC-ARF data: ps_ortho_processing_before_input_gcp.py will set up a PhotoScan project and align photographs. If Ground Control Points (GCPs) are available, then the script will stop and prompt you to manually locate them in the PhotoScan project. If no GCPs are available, the script will complete the whole PhotoScan processing workflow without (obviously accuracy of data is significantly reduced). This step is not automated. ps_ortho_processing_after_input_gcp.py is run after the and placement of Ground Control Points.

Ground Control Points
Coordinates of GCPs in CSV format can be added to PhotoScan. The user will then need to 'drag and drop' the marker locations to their locations visible in the photographs input. This needs to be done for all photographs each GCP is visible in.
Note: once a couple of GCPs have been located in multiple respective photographs; the 'reproject' button (looks like a recycling symbol) will automatically place the remaining photo. These will still need to be accurately places, but will save a lot of time nevertheless.

Running a script:

• Update config file (template is located in /templates/ps_workflow.cfg).
• As airborne, in the rsg-photoscan virtual machine, run:

/opt/photoscan/photoscan.sh -r ps_ortho_processing_before_input_gcp.py -c [CONFIG]

• If no GCPs have been input in config file, (gcp_csv_path = None) or if gcp_csv_path does not exist, then ps_ortho_processing_before_input_gcp.py will run through the whole PhotoScan workflow without GCPs.
• If a path to GCP CSV has been input into the config file, these GCP coordinates will need to be manually positioned to their correct locations on the aligned photographs. Once this has been achieved, the second script can be run:

/opt/photoscan/photoscan.sh -r ps_ortho_processing_before_after_gcp.py -c [CONFIG]

Config Information
The same config template is used.
The project directory (defined in config file) is the location of the PhotoScan project file (*.psx) and other data produced whilst processing.
The output directory (also defined in config) is where the Point Cloud, DEM and/or Orthomosaic is exported, if the associated parameters are True in config file. If the output directory does not exist, then it will be created.

Creating Delivery

This additional processing service will be delivered as additional items in the otherwise conventional digital camera delivery using the following structure:

Dirs	Sub dir	Example Files	Comments
		ES17_126-2017_172.kml	Google earth file containing Fenix/Owl/camera positions
		Read_Me-20171017.pdf	Instructions for use and description of dataset, plus any problems encountered
		Read_Me-20180222_orthomosaic.pdf	Instructions for use and description of photogrammetry products
dem			Digital Surface Model(s) produced from PhotoScan.
		PHASEONE-IXU-ES17_126-2017172_site-1_dem-utm30n.dem	Digital Surface Model in ENVI format.
		PHASEONE-IXU-ES17_126-2017172_site-1_dem-utm30n.hdr	Header for accompanying Digital Surface Model in ENVI format.
doc			Useful documents
		camera_data_quality_report2012.pdf	Camera data quality report
		RCD105_SN21_Calibration_Certificate.pdf	Camera Calibration Certificate
eventfile		RCD105-GB08_02-2009078a-ImageEvents.csv	CSV file containing pos/att info per photograph event (may be missing if camera crashed)
photographs		RCD105-GB08_02-2009078a-00001.tif	Tagged tif files of each photograph in area of interest
thumbnails		RCD105-GB08_02-2009078a-00001.jpg	JPEG thumbnails of each photograph in area of interest