IAP Version 2.3.0

V2.3.0 (July 14, 2020)

• Removed SBML read/write
• Removed 3-D animations (to be compatible with OpenJDK and higher Java versions)
• Fixed file count parsing on dataset loading from int to long
• Added additional error handling to make dataset loading more robust
• Application can compile with OpenJDK and possibly higher Java versions

IAP Version 2.1.0

V2.1.0 (April 10, 2017)

• Extended import and data processing functions

IAP Version 2.0.7

V2.0.7 (January 20, 2017)

• New/updated blocks:
  • width/height calculation for fluorescence images
  • external command execution (execution of external shell commands and result import)
  • volume calculation for all image modalities
  • curvature calculations based on skeleton
• Update default parameters and software maintenance
  • top/side option while creating data set (Settings -> File Import)

IAP Version 2.0.6

V2.0.6 (October 20, 2016)

• Added IAP dataset detection while using the file browser to open an IAP-dataset
• Added export function for archiving datasets
• Include PLY point cloud visualization tool
• Update default parameters and fix some bugs

IAP Version 2.0.5

V2.0.5 (June 1, 2016)

• Added missing (in version 2.0.4) plugin list (version 2.0.4 is not working)
• Remaining changes from V2.0.3 are listed below

V2.0.4 (May 29, 2016)

• New command buttons for application exit (quit) and window close functions.
  The new quit command is useful when using the command line interface of IAP
  (before Ctrl+C would have to be used).
• The outlier marking commands (image browser context menu) allow selecting
  or marking of images according to the exact snapshot fine time. This means,
  you can mark images that were created after (or before) a specific image has
  been taken. Before only images from a specific day or before a specific day
  could be marked.

IAP Version 2.0.3

V2.0.3 (April 9, 2016)

First new version which is released on GitHub. Source code repository content has been
transferred to GitHub.

• A new filter HSV block has been added, the combination of multiple filters
  works like when using the Lab filter block. The old HSV filter is still
  available, but added to the block group 'Depricated'.
• A new rank filter block makes it easy to extract the max/mean/median/min/
  variance/... from an image (with variable kernel size). This command
  should be used early on, as it does not work with images that have been
  segmented into fore- and background.

Further additions and bug fixes

• The analysis block for morphological operations has been corrected to properly
  use a round mask of the given size.
• The histogram block also saves the bin size (useful as a reference, if the number
  of bins has been adjusted from the default value).

IAP Version 2.0.2

V2.0.2 (July 27/Sep 2, 2015)

Functions related to our award-winning (1st place) approach for foreground-/ background-separation and leaf counting, as described in our presentation and publication in connection with the CVPPP 2014 workshop in Zurich:

• A new analysis block to count the number of different colors in the VIS images has been added (BlCountColors).
• Detect leaf center points block: calculates a eucledian distance map and detects peaks in that image. As a result center points in convex areas are detected (e.g. leaves of rosette plants) (BlDetectLeafCenterPoints).
• Label leaf areas using advanced graph-based leaf area split line calculations. Only IAP incorporates an advanced graph library (VANTED) utilizing graph visualisation and manipulation commands (BlDetectLeafCenterPoints).

Further additions and bug fixes:

• The calculation of the convex hull length was incorrect. This problem has been resolved. Previous calculations of the convex hull length and of the convex hull compactness are either incorrect (in about 10% of the cases) or missing in the result table row (in about 90% of the cases). Other values, such as convex hull area are not affected by this bug.
• For testing purposes a image resize block was added.
• Datasets can be created from a list of files using the 'Load or Create Dataset' > 'Create Dataset from Files' commands.