mirror of
https://github.com/bec-project/bec_widgets.git
synced 2025-07-14 03:31:50 +02:00
111 lines
4.9 KiB
Markdown
111 lines
4.9 KiB
Markdown
(user.widgets.image_widget)=
|
|
|
|
# Image widget
|
|
|
|
````{tab} Overview
|
|
|
|
The Image widget is a versatile tool designed for visualizing both 1D and 2D data, such as camera images or waveform data, in real-time. Directly integrated with the `BEC` framework, it can display live data streams from connected detectors or other data sources within the current `BEC` session. The widget provides advanced customization options for color maps and scale bars, allowing users to tailor the visualization to their specific needs.
|
|
|
|
## Key Features:
|
|
- **Flexible Integration**: The widget can be integrated into [`BECDockArea`](user.widgets.bec_dock_area), or used as an individual component in your application through `BEC Designer`.
|
|
- **Live Data Visualization**: Real-time plotting of both 1D and 2D data from detectors or other data sources, provided that a data stream is available in the BEC session.
|
|
- **Support for Multiple Monitor Types**: The Image widget supports different monitor types (`'1d'` and `'2d'`), allowing visualization of various data dimensions. It can automatically determine the best way to visualise the data based on the shape of the data source.
|
|
- **Customizable Color Maps and Scale Bars**: Users can customize the appearance of images with various color maps and adjust scale bars to better interpret the visualized data.
|
|
- **Real-time Image Processing**: Apply real-time image processing techniques directly within the widget to enhance the quality or analyze specific aspects of the data, such as rotation, logarithmic scaling, and Fast Fourier Transform (FFT).
|
|
- **Data Export**: Export visualized data to various formats such as PNG, TIFF, or H5 for further analysis or reporting.
|
|
- **Interactive Controls**: Offers interactive controls for zooming, panning, and adjusting the visual properties of the images on the fly.
|
|
|
|
|
|
````
|
|
|
|
````{tab} Examples - CLI
|
|
|
|
`ImageWidget` can be embedded in [`BECDockArea`](user.widgets.bec_dock_area), or used as an individual component in your application through `BEC Designer`. The command-line API is the same for all cases.
|
|
|
|
## Example 1 - Visualizing 2D Image Data from a Detector
|
|
|
|
In this example, we demonstrate how to add an `ImageWidget` to a [`BECDockArea`](user.widgets.bec_dock_area) to visualize live 2D image data from a connected camera detector.
|
|
|
|
```python
|
|
# Add a new dock with BECFigure widget
|
|
dock_area = gui.new()
|
|
img_widget = dock_area.new().new(gui.available_widgets.Image)
|
|
|
|
# Add an ImageWidget to the BECFigure for a 2D detector
|
|
img_widget.image(monitor='eiger', monitor_type='2d')
|
|
img_widget.title = "Camera Image - Eiger Detector"
|
|
```
|
|
|
|
## Example 2 - Visualizing 1D Waveform Data from a Detector
|
|
|
|
This example demonstrates how to set up the Image widget to visualize 1D waveform data from a detector, such as a line detector or a spectrometer. The widget will stack incoming 1D data arrays to construct a 2D image.
|
|
|
|
```python
|
|
# Add a new dock with BECFigure widget
|
|
dock_area = gui.new()
|
|
img_widget = dock_area.new().new(gui.available_widgets.Image)
|
|
|
|
# Add an ImageWidget to the BECFigure for a 2D detector
|
|
img_widget.image(monitor='waveform', monitor_type='1d')
|
|
img_widget.title = "Line Detector Data"
|
|
|
|
# Optional: Set the color map and value range
|
|
img_widget.colormap = "plasma"
|
|
img_widget.vrange= [0, 100]
|
|
```
|
|
|
|
## Example 3 - Real-time Image Processing
|
|
|
|
The `Image` provides real-time image processing capabilities, such as rotating, scaling, applying logarithmic scaling, and performing FFT on the displayed images. The following example demonstrates how to apply these transformations to an image.
|
|
|
|
```python
|
|
# Rotate the image by 90 degrees (1,2,3,4 are multiplied by 90 degrees)
|
|
img_widget.num_rotation_90 = 1
|
|
|
|
# Transpose the image
|
|
img_widget.transpose = True
|
|
|
|
# Apply FFT to the image
|
|
img_widget.fft = True
|
|
|
|
# Set logarithmic scaling for the image display
|
|
img_widget.log = True
|
|
|
|
# Set autorange for the image color map
|
|
img_widget.autorange = True
|
|
img_widget.autorange_mode = 'mean'# or 'max'
|
|
```
|
|
<!--
|
|
## Example 6 - Setting Up for Different Detectors
|
|
|
|
The Image Widget can be configured for different detectors by specifying the correct monitor name and monitor type. Here's how to set it up for various detectors:
|
|
|
|
### For a 2D Camera Detector (e.g., 'eiger')
|
|
|
|
```python
|
|
# For a 2D camera detector
|
|
img_widget = fig.image(monitor='eiger', monitor_type='2d')
|
|
img_widget.set_title("Eiger Camera Image")
|
|
```
|
|
|
|
### For a 1D Line Detector (e.g., 'waveform')
|
|
|
|
```python
|
|
# For a 1D line detector
|
|
img_widget = fig.image(monitor='waveform', monitor_type='1d')
|
|
img_widget.set_title("Line Detector Data")
|
|
```
|
|
|
|
```{note}
|
|
Since the Image Widget does not have prior information about the shape of incoming data, it is essential to specify the correct `monitor_type` when setting up the widget. This ensures that the data is processed and displayed correctly.
|
|
``` -->
|
|
|
|
|
|
````
|
|
|
|
````{tab} API
|
|
```{eval-rst}
|
|
.. include:: /api_reference/_autosummary/bec_widgets.cli.client.Image.rst
|
|
```
|
|
````
|