Sample Programs¶
Image processing¶
Display an image.
Display and graphically interact with an ROI.
Display an image in a WPF context.
Display and graphically interact with an ROI.
Initialize and release the eVision library.
Check for a specific license.
Load an image and perform a simple processing on it.
Create an ERegion and use it to restrict eVision processing to its domain.
Create an ERegion using the ERegionFreeHandPainter.
Apply filter operations on a loaded image.
Compute the direct Fourier transform.
Compute the inverse Fourier transform.
Retrieve one component of a color image after converting it from RGB to a given color space.
Perform an HDR Fusion on a specific set of images.
Use the EGrabberBridge functionality to import and use images produced by an object eGrabber with eVision.
Use eVision in a C++ DLL.
3D Processing¶
Use most of the features of the Easy3D class E3DViewer.
Convert 3D files formats.
Use a point picking.
Display an E3DViewer in a WPF context.
Apply photometric stereo to several images to retrieve their albedo, gradients, curvatures or height map.
Generate a mesh from a point cloud.
Generate a ZMap from a mesh or a point cloud.
Load a depth map.
Apply a 2D operator (the text reading tool EasyOCR2) on the gray scale pixel values.
Load and display point clouds in multiple instances of the class E3DViewer.
Measure the warpage of a PCB with Easy3D.
Acquire depth maps from a Coaxlink 3D LLE frame grabber and optionally save them.
Compute and save the calibration model.
Apply the calibration to a depth map.
Save the resulting point cloud.
Create a depth map from a series of profile images using the software laser line extractor.
Load an image.
Set the X, Y and Z resolutions.
Display the corresponding point cloud and the extracted 3D objects.
Match a sample (point cloud or ZMap) on a reference (3D mesh, point cloud or ZMap).
Align a sample (point cloud or ZMap) on a reference (3D mesh, point cloud or ZMap).
Merge several point clouds by using a calibration procedure with a specific object.
Matching and Measurement¶
Load an image and apply a gauge from EasyGauge, chosen between a Point Gauge, a Line Gauge, a Rectangle Gauge, a Circle Gauge, a Wedge Gauge and a Polygon Gauge.
Implement graphical edition of the gauge geometry.
Set and display the main parameters of the gauges: the transition polarity, the choice of measure and various display options.
Load an image and apply a gauge from EasyGauge, chosen between a Rectangle Gauge and a Circle Gauge.
Create a region corresponding to the gauge from the result.
Perform a blob encoding operation on it.
Use the class EPolygonGauge of the EasyGauge library.
Edit the geometry of the gauge and change the main parameters.
Configure various display options.
Load an image.
Move and size the region of interest to define the pattern.
Learn the pattern in the region of interest.
Change the tolerances using the Tolerances menu.
Find the pattern using the Find menu.
Use EasyFind with vectorized learning patterns. In this mode, learning is done on collections of 2D geometrical shapes rather than rasterized patterns.
Open a DXF or eVision vector model with File > Open Model. Right-click to change the polarity of a transition.
Save the vector model with the edited polarity.
Learn the pattern with the button Learn.
Open a search image and find the pattern with the button Find.
Learn a pattern from a region of interest in an image.
Find one or several instances of that pattern in the same image.
Specify the inspection area.
Select fiducials for the localization and the alignment of the inspection area.
Train the method and apply it on new images.
Find blobs (objects or holes that have the same gray level range) in the image.
Keep only the blobs whose area is in a given range.
Deep Learning Inspection¶
Train an EasyClassify tool in console mode.
Perform an inference with EasyClassify.
Display the results.
Perform a multithread inference with EasyClassify.
Implement external and internal multithreading.
Train an EasySegment Supervised tool in console mode.
Perform an inference with EasySegment Supervised.
Display the results.
Perform a multithread inference with EasySegment Supervised in console mode.
Implement external and internal multithreading.
Train an EasySegment Unsupervised tool in console mode.
Perform an inference with EasySegment Unsupervised.
Display the results.
Train an EasyLocate tool in console mode.
Perform an inference with EasyLocate.
Display the results.
Perform a multithread inference with EasyLocate.
Implement external and internal multithreading.
Text and Code Reading¶
Read a bar code, a data matrix and a QR code in an image with a single read call.
Read a 1D bar code in an image.
Read a mail bar code in an image.
Read a data matrix code in an image.
Read a QR code in an image.
Read a text inside the ROI of an image using EasyOCR (superseded by EasyOCR2).
Use a configuration based on a OCR font file (.ocr).
Read a text inside the ROI of an image.
Read all the texts in an image with a single read call.
Load a model.
Read all the texts in an image with a single read call.
Load a model.
Set a topology.
Applicative Processing Tools¶
Load an image and the corresponding EasySpotDetector model.
Perform the detection of spots (particles and scratches).
Display the results over the image.
Python Specific¶
Acquire images through the eGrabber camera API.
Manipulate the images.
Acquire images through the OpenCV camera API.
Manipulate the images.
Display a 3D resource (cloud or mesh) within an eVision 3DViewer using OpenGL and SDL2.
Learn a pattern.
Find it in an image using EasyFind in a Qt application.
Make subpixel measurements with EasyGauge in a Qt application.
Acquire images through the VimbaX camera API.
Manipulate the images.
Make image acquisition in a web server.
Perform image processing.
Broadcast the images using HTTP to any remote client through a web browser.
Perform and rotate and scale an image.
Display the image using the Tkinter GUI framework.