![]() ![]() png), "description", which is a text that The entries "icon", which should be the path of an icon (preferably. The run function may return a dictionary with Of the script is called with the module's type as string argument. The script is treated like an invisible macro module. ![]() (which just points to the Python file and declares a title for display in a combo box). Sets the size of the image preview thumbnails in pixel.Ĥ.3.7.1. How to define your own badge scriptsĪ badge script consists of a single. Shows an image preview for an image connector when a single module is selected. Sets the threshold zoom factor below which the verbose details are not displayed. Sets the threshold zoom factor below which the details are not displayed. Sets the font size for the connector detail info. See Section 4.3.7.1, “How to define your own badge scripts” for how to define your own badge scripts.Įnables detailed information for ML image, Inventor, or Base objects currentlyĪvailable on the connectors when a single module is selected. Users aware of certain properties of a module. Select a script that provides a badge icon for modules. Shows the image states by coloring the connectors. Sets the grid size in the workspace to which the modules snap when moved. Sets the font size of the module name in the display (number referring to a zoom of 100%). Sets the background color for notes, see Section 3.12, “Using Notes”. Sets the background color for module groups, see Section 3.11, “Using Groups”. Other modules/networks will be displayed with the given global zoom factor upon double-clicking the networks space or using the button (Show the whole network) in the toolbar. Only applicable to modules and networks that do not fill the network space automatically. To change the halo colors of the selected modules and the modules attached to them, edit the settings of Selected, Source, and Destination by clicking on the respective color field. This may considerably slow down the startup.Ĭlassic (Default): The halo is rendered as classic halo effect.Īlternative: The halo is rendered as rectangle around the module. Gives the number of recent networks to be loaded automatically on MeVisLab startup. script file in the default text editor at the line in which the GUI control is defined. When enabled, CTRL+left-clicking a GUI control in a module panel opens the. (including window size and position) to the state (open, minimized, positions, etc.) when the network was last saved.Įnables/disables debugging module panels. If selected, opening a network restores all module panels For more details, see Section 3.15, “Network Selector”. If selected, pressing CTRL+ TAB (or SHIFT+ CTRL+ TAB) does not switch directly to the next or previous network document, but shows a network selector preview. Show network selector when switching documents via CTRL-Tab Auto-saved copies are deleted when the according networks are saved. ![]() This allows for restoring in case of system crashes. If selected, MeVisLab networks are auto-saved as. Selecting Show Window → Panel from the module context menu). Reloaded when reloading the module panel (by double-clicking the module or Gives the amount of texture memory (texture RAM, TRAM) on the graphics card to be used for MeVisLab texture processing, for example in the View2D module.ĭefines the percentage of texture memory that the GVR volume renderer may use. Total Texture Memory on Graphics Card (MB) Otherwise, a new ML host is used that implements an optimized multi-threading for the ML. If checked, the classic ML host (the only available option before MeVisLab 2.5) is used. For more details on multi-threading, see Section 27.7, “Multi-threading in MeVisLab”. Gives the number of parallel threads for image processing. Maximum Threads Used for Image Processing For details, see the ML Programming Guide, “ Optimizing Data Flow in Module Networks”. ![]() For 2 GB RAM, a value of 512 MB is well-tested. Cache sizes too large might cause a collapse of your system because of reduced memory for other programs. Reducing the cache size will slow down the image processing pipelines because images will be recalculated more frequently in individual modules. Use the default settings if in doubt.ĭefines the memory available for caching (intermediate) ML image tiles/pages within a network of image processing modules. The optimal Resources settings depend on the system and platform. The user currently signed in at this computer. ![]()
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