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| QWidget * | getSettingsWidget (QWidget *parent) override |
| | returns a widget to change parameters of this plugin.
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| std::vector< uint > | sampleImages (const std::vector< unsigned int > &imageList, Progressable *receiver, volatile bool *stopped, bool useCuda, LogFileParent *logFile) override |
| | sampleImages Create an keyframe list with indices of the keyframes. The algorithm reports progress to the Progressable *receiver by calling Progressable::slot_makeProgress. If the *stopped bool is set to true the algorithm should abort the calculations and exit.
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| QString | getName () const override |
| | getName Returns the plugin name
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| void | initialize (Reader *reader, QMap< QString, QVariant > buffer, signalObject *sigObj) override |
| | initialize is called after new images have been loaded. the plugin parameters can be selected based on the images.
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| void | setSettings (QMap< QString, QVariant > settings) override |
| | setter for plugin's settings
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| QMap< QString, QVariant > | generateSettings (Progressable *receiver, bool useCuda, volatile bool *stopped) override |
| | generateSettings tries to generate the best settings for the current input
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| QMap< QString, QVariant > | getSettings () override |
| | getter for plugin's settings
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| virtual std::vector< uint > | sampleImages (const std::vector< uint > &imageList, Progressable *receiver, volatile bool *stopped, bool useCuda, LogFileParent *logFile)=0 |
| | sampleImages selects the keyframes from the given images. The computation is based on the images provided by the given Reader. The imageList provides indices for the currently selected keyframes. This way the current selection can be taken in account in the calculation. Since the algorithm can be very time consuming, it is recommended to report progress to the given Progressable by invoking Progressable::slot_makeProgress. It should be possible to abort calculation by setting the value of stopped to true. Therefore it is necessary to repeatedly check its state. To speedup calculation, data can be buffered to accelerate the next call of sampleImages. On some systems the gpu can be utilized for acceleration as well, but only if useCuda is true. See following example implementation for sampleImages:
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