# eVision

> eVision 26.10.0-beta.2.dev documentation


2026, Euresys

## Pages in this subsection

- [Using eVision](index.html.md): Index of the Using eVision guide, covering basic operations and every eVision library and tool, organized by category.
- [Basic Operations](basic_operations/index.html.md): Overview of eVision's basic operations: pixel containers, memory allocation, drawing, ROIs, regions, masks, frames, and shapes.
- [Image Operations](basic_operations/images/index.html.md): This section shows how to use images throughout **eVision**.
- [Pixel Containers and Files](basic_operations/images/pixel_containers_and_files.html.md): Describes eVision's image, depth map, and point cloud pixel containers, supported color types, and compatible image file formats.
- [Loading a Pixel Container File](basic_operations/images/loading_a_pixel_container_file.html.md): Explains how to load images, depth maps, and point cloud files (CSV, OBJ, PCD, PLY, XYZ) into eVision pixel containers.
- [Saving a Pixel Container File](basic_operations/images/saving_a_pixel_container_file.html.md): Explains how to save eVision images, depth maps, and point clouds to disk, including JPEG and JPEG2000 compression quality settings.
- [Memory Allocation](basic_operations/images/memory_allocation.html.md): Explains internal versus external memory allocation for eVision image buffers, including linking third-party buffers to eVision images.
- [Drawing in Images](basic_operations/images/drawing_in_images.html.md): Explains eVision's Draw methods and draw adapters for rendering images, ROIs, and tool overlays on Windows, Qt, or custom contexts.
- [3D Rendering of 2D Images](basic_operations/images/3d__rendering_of_2d_images.html.md): Explains eVision's 3D rendering functions that visualize 2D gray-level images as height maps and color image histograms as RGB scatter plots.
- [Regions and ROIs](basic_operations/regions/index.html.md): This section shows how to use regions and ROIs throughout **eVision**.
- [Regions Of Interest (ROI)](basic_operations/regions/regions_of_interest.html.md): Explains eVision ROI properties: width, height, origin, attachment to a parent image, hierarchical nesting, cropping, and resizing.
- [Arbitrarily Shaped ROI (ERegion)](basic_operations/regions/arbitrarily_shaped_roi__eregion_.html.md): Explains ERegion, eVision's arbitrarily shaped region of interest: how to create, combine, transform, and draw regions beyond rectangular ROIs.
- [Flexible Masks](basic_operations/regions/flexible_masks.html.md): Compares rectangular ROIs with flexible masks and explains how EasyImage and EasyObject use BW8 masks to restrict processing to non-rectangular areas.
- [Frames and Alignment](basic_operations/frame_and_alignment.html.md): Explains eVision's EFrame class for representing local, world, and sensor reference frames and mapping geometric objects between them.
- [Common Data Types](basic_operations/common_data_types/index.html.md): Overview of eVision's common data types: geometric shapes and eVision's eVectors.
- [Vectors](basic_operations/common_data_types/vector_types_and_main_properties.html.md): Describes eVision's EVector-based pixel vector types for profiles, paths, histograms, and peaks, and how to create, fill, and draw them.
- [Geometrical Shapes](basic_operations/common_data_types/geometrical_shapes.html.md): Describes eVision's geometrical shape classes (rectangle, circle, wedge, line, polygon, ellipse) and how they differ from regions.
- [Error Reporting](basic_operations/error_reporting.html.md): When an **eVision** function fails, it throws an exception that contains an error code and a descrip...
- [Utility Functions](basic_operations/utils/index.html.md): This sections presents utilitary operations in **eVision** for time measurement and installation and...
- [Timing](basic_operations/utils/timing.html.md): Use the following functions to time a particular piece of code:
- [Locating Installation Folders](basic_operations/utils/retrieving_the_installation_folders_programmatically.html.md): Lists the Easy object methods for programmatically retrieving eVision's sample images, sample programs, and resources installation paths.
- [General Purpose Libraries](general_purpose/index.html.md): Overview of eVision's general purpose libraries EasyImage and EasyColor for gray-level and color image pre-processing.
- [EasyImage - Pre-Processing Images](general_purpose/easyimage/index.html.md): Overview of EasyImage's gray-level pre-processing functions: thresholding, filtering, geometric transforms, statistics, and feature detectors.
- [Intensity Transformation](general_purpose/easyimage/intensity_transformation.html.md): Explains EasyImage's intensity transformations: gain/offset, normalization, uniformization, and lookup tables to adjust pixel gray levels.
- [Thresholding](general_purpose/easyimage/thresholding.html.md): Explains EasyImage's automatic, manual, and histogram-based thresholding methods for segmenting images into bi- or tri-level classes.
- [Profile](general_purpose/easyimage/profile.html.md): Explains how to sample image profiles along lines, paths, or contours in eVision, and analyze them for peaks and transitions.
- [Arithmetic and Logic](general_purpose/easyimage/arithmetic_and_logic.html.md): Explains EasyImage's arithmetic and logic operations (Oper) for combining, comparing, and masking image pixels with constants or other images.
- [Linear Filtering](general_purpose/easyimage/linear_filtering.html.md): Explains EasyImage's linear filtering (convolution) functions, including predefined kernels and how to build a custom EKernel.
- [Non-Linear Filtering](general_purpose/easyimage/non-linear_filtering.html.md): Explains EasyImage's morphological non-linear filters: erosion, dilation, opening, closing, top-hat, thinning, and hit-and-miss transform.
- [Geometric Transforms](general_purpose/easyimage/geometric_transforms.html.md): Explains EasyImage's geometric transforms: image re-alignment, mirroring, resizing, scale/rotate, shrinking, and LUT-based unwarping.
- [Noise Reduction and Estimation](general_purpose/easyimage/noise_reduction_and_estimation.html.md): Explains EasyImage's spatial and temporal noise reduction methods (convolution, median, recursive/moving average) and noise estimation functions.
- [Scalar Gradient](general_purpose/easyimage/scalar_gradient.html.md): Explains EasyImage's GradientScalar function for computing gradient direction or magnitude maps from a gray-level image using a lookup table.
- [Vector Operations](general_purpose/easyimage/vector_operations.html.md): Explains EasyImage's vector operations for extracting and analyzing 1D image data via projection and profile sampling of peaks and transitions.
- [Canny Edge Detector](general_purpose/easyimage/canny_edge_detector.html.md): Explains EasyImage's Canny edge detector, its smoothing scale and hysteresis threshold parameters, for producing a binary edge map.
- [Harris Corner Detector](general_purpose/easyimage/harris_corner_detector.html.md): Explains EasyImage's Harris corner detector, its integration scale, threshold, and sub-pixel parameters for finding points of interest.
- [Overlay](general_purpose/easyimage/overlay.html.md): Explains EasyImage's Overlay function for compositing a color or grayscale image onto a color image at a given position.
- [Operations on Interlaced Video Frames](general_purpose/easyimage/operations_on_interlaced_video_frames.html.md): Explains EasyImage's functions for realigning, rebuilding, deinterlacing, and interlacing video frames to remove interlacing artifacts.
- [Computing and Using Image Statistics](general_purpose/easyimage/computing_image_statistics.html.md): Explains EasyImage's tools for computing sliding window statistics, histograms, equalization, focus measurement, and pixel statistics.
- [Fourier Transform](general_purpose/easyimage/fourier_transform.html.md): Explains EasyImage's Fourier transform for converting images to the frequency domain, and its Packed and Complex Extended formats.
- [Gabor Filter](general_purpose/easyimage/gabor_filter.html.md): Explains EasyImage's Gabor filter for texture analysis, detailing its sigma, gamma, theta, lambda, and psi parameters.
- [HDR Fusion](general_purpose/easyimage/hdr_fusion.html.md): Explains EasyImage's HDR fusion, which merges multiple exposures and tone-maps them, detailing the Debevec, Robertson, and Mertens mergers.
- [Image Stitching](general_purpose/easyimage/image_stitching.html.md): Explains EasyImage's EImageStitcher for combining overlapping images, covering grid setup, incremental mode, learning, and debugging.
- [EasyColor - Pre-Processing Color Images](general_purpose/easycolor/index.html.md): Overview of EasyColor's color image pre-processing: color systems, LUT-based transforms, Bayer decoding, component operations, and RGB/BGR conversion.
- [Bayer Conversion](general_purpose/easycolor/bayer_conversion.html.md): Explains EasyColor's Bayer pattern demosaicing, its configurations, and the six interpolation modes with their speed and quality trade-offs.
- [Lookup Table Operations](general_purpose/easycolor/lookup_table.html.md): Explains EasyColor's lookup table (LUT) operations for color balance, gamma precompensation, color calibration, and gain/offset adjustment.
- [Matching and Measurement](matching_and_measurement/index.html.md): Overview of eVision's pattern matching and measurement libraries: EasyObject, EasyGauge, EasyFind, EasyMatch, and EChecker.
- [EasyObject - Analyzing Blobs](matching_and_measurement/easyobject/index.html.md): Introduces EasyObject, eVision's blob (connected-component) analysis library, with links to encoding, feature computation, and blob selection.
- [Encoding an Image](matching_and_measurement/easyobject/image_encoder.html.md): Explains how EasyObject's image encoder segments pixels into layers with configurable segmenters, connexity, and continuous mode for blob building.
- [Objects, Holes and their Features](matching_and_measurement/easyobject/objects_holes_features.html.md): Reference for EasyObject blob and hole features, including gravity center, Feret box, moments, ellipse of inertia, and convex hull.
- [Selecting and Sorting Blobs](matching_and_measurement/easyobject/selecting_and_sorting_blobs.html.md): How to use EObjectSelection to filter and sort EasyObject blobs and holes by position, region, rectangle, or numeric feature criteria.
- [Object Template Matcher](matching_and_measurement/easyobject/object_template_matcher.html.md): Explains EObjectTemplateMatcher, which aligns and matches EasyObject blob positions against a reference template using rigid alignment.
- [EChecker - Validating Golden Templates](matching_and_measurement/easyobject/echecker.html.md): Describes EChecker, eVision's golden-template inspection tool that trains a statistical model from reference images and flags defects during inspection.
- [EasyGauge - Measuring down to Sub-Pixel](matching_and_measurement/easygauge/index.html.md): Introduces EasyGauge, eVision's sub-pixel measurement library for fitting lines, circles, rectangles, wedges, and polygons to image edges.
- [Differences with the Legacy API](matching_and_measurement/easygauge/porting_from_legacy_gauge.html.md): Describes the API differences between the new and legacy EasyGauge libraries and how to port an application from the legacy gauge API.
- [Legacy EasyGauge](matching_and_measurement/easygauge/legacy_easygauge/index.html.md): Index of the legacy EasyGauge API topics covering workflow, gauge definitions, transition finding, calibration, and image unwarping.
- [Workflow](matching_and_measurement/easygauge/legacy_easygauge/workflow.html.md): Overview of the legacy EasyGauge workflow: uncalibrated, calibrated, and grouped gauging approaches for measuring parts to sub-pixel accuracy.
- [Gauge Definitions](matching_and_measurement/easygauge/legacy_easygauge/gauge_definitions.html.md): Reference for the legacy EasyGauge point, line, rectangle, circle, wedge, and polygon gauge classes, their placement, and measurement usage.
- [Find Transition Points Using Peak Analysis](matching_and_measurement/easygauge/legacy_easygauge/find_transition_points_using_peak_analysis.html.md): Explains how the legacy EPointGauge locates edge transition points via peak analysis, including thresholding, filtering, and peak selection.
- [Find Shapes Using Geometric Models](matching_and_measurement/easygauge/legacy_easygauge/find_shapes_using_geometric_models.html.md): Describes the legacy EasyGauge line, circle, rectangle, wedge, and polygon gauges for fitting geometric models to edges, with outlier rejection.
- [Gauge Manipulation: Draw, Drag, Plot, Group](matching_and_measurement/easygauge/legacy_easygauge/gauge_manipulation_draw_drag_plot_group.html.md): How to draw, drag, plot, and group legacy EasyGauge gauges for graphical interaction and building hierarchical measurement tools.
- [Calibration and Transformation](matching_and_measurement/easygauge/legacy_easygauge/calibration_and_transformation.html.md): Describes field-of-view calibration concepts and how world-to-sensor transforms like scaling, skew, perspective, and distortion affect gauging.
- [Calibration Using EWorldShape](matching_and_measurement/easygauge/legacy_easygauge/calibration_using_eworldshape.html.md): How to calibrate a field of view with the legacy EWorldShape class using estimation, landmark points, or automatic dot-grid target analysis.
- [The Calibration Model](matching_and_measurement/easygauge/legacy_easygauge/the_calibration_model.html.md): Details the field-of-view, advanced, and empirical calibration models used by the legacy EWorldShape class and their tunable parameters.
- [Unwarp an Image](matching_and_measurement/easygauge/legacy_easygauge/unwarp_an_image.html.md): Explains image calibration concepts and how to unwarp a distorted image into a rectified, distortion-free image using EWorldShape.
- [EasyFind - Matching Geometric Patterns](matching_and_measurement/easyfind/index.html.md): Overview of EasyFind, eVision's fast geometric pattern-matching library, with links to its principles, learning, and finding pages.
- [Purpose and Principles](matching_and_measurement/easyfind/purpose_and_principles.html.md): Explains EasyFind's feature-point matching technology, its accuracy and robustness, and how it compares to EasyMatch for pattern location.
- [Learn a Pattern from Image(s)](matching_and_measurement/easyfind/learning.html.md): How to learn an EasyFind pattern from one or more images, including multi-pattern learning, pattern type, light balance, and feature points.
- [Learn a Pattern from Vectors](matching_and_measurement/easyfind/learn_the_model_from_vectors.html.md): How to learn an EasyFind pattern from geometric shapes or a DXF vector file, including scaling, centering, and transition orientation.
- [Find Matches](matching_and_measurement/easyfind/finding.html.md): Explains EasyFind's Find Matches step: score interpretation, contrast mode, angle and scale tolerances, overlap filtering, and search timeout.
- [EasyMatch - Matching Area Patterns](matching_and_measurement/easymatch/index.html.md): Introduces EasyMatch, eVision's pixel-by-pixel pattern matching library for locating rotated, scaled, or color patterns in images.
- [Learn a Pattern](matching_and_measurement/easymatch/learning_process.html.md): How to learn an EasyMatch pattern from an image, covering ideal pattern characteristics, multi-pattern learning, and image pyramid parameters.
- [Find Matches](matching_and_measurement/easymatch/matching_process.html.md): Explains the EasyMatch Find Matches workflow: angle and scale tolerances, correlation modes, overlap filtering, and pyramid matching parameters.
- [Text and Code Reading](text_and_code_reading/index.html.md): Overview of eVision's text and code reading libraries: bar code, matrix code, QR code, and OCR tools, both classic and deep-learning based.
- [EasyBarCode - Reading Bar Codes](text_and_code_reading/easybarcode/index.html.md): EasyBarCode
- [Using EasyBarCode](text_and_code_reading/easybarcode/easybarcode2.html.md): Explains EasyBarCode2, eVision's 1D bar code reader: symbologies, checksum validation, grading, grid reading, timeouts, and error correction.
- [EasyMailBarCode - Reading Mail Bar Codes](text_and_code_reading/easybarcode/easymailbarcode.html.md): Explains EasyMailBarCode, eVision's reader for 4-state postal bar codes, covering symbologies, orientation, checksum, and advanced parameters.
- [EasyBarCode1 - Reading Bar Codes (deprecated)](text_and_code_reading/easybarcode/easybarcode.html.md): Documents the deprecated EasyBarCode library for reading 1D bar codes and explains why to migrate to EasyBarCode2 instead.
- [EasyDeepOCR - Reading Texts with Deep Learning](text_and_code_reading/easydeepocr/index.html.md): Introduces EasyDeepOCR, eVision's deep-learning OCR library, its scope, structured-text rules, custom use case optimization, and workflow.
- [Detailed Usage](text_and_code_reading/easydeepocr/detailed_usage.html.md): Detailed guide to EasyDeepOCR: reading text, scoring, drawing results, specifying topologies, text angle, optimization, and the split pipeline.
- [Retraining a Model](text_and_code_reading/easydeepocr/retraining_a_model.html.md): How to retrain EasyDeepOCR's location, orientation, and recognition neural networks in Deep Learning Studio or via the API for custom use cases.
- [Setting the Parameters](text_and_code_reading/easydeepocr/setting_the_parameters.html.md): How to configure EasyDeepOCR's deep learning execution settings and build a sample list for optimizing the reader on a custom use case.
- [EasyOCR - Reading Texts](text_and_code_reading/easyocr1.html.md): Explains EasyOCR, eVision's template-matching OCR library for reading short texts, covering font learning, segmentation, and recognition parameters.
- [EasyOCR2 - Reading Complex Texts](text_and_code_reading/easyocr2/index.html.md): Introduces EasyOCR2, eVision's optical character recognition tool for reading short texts using topology-guided detection and classifiers.
- [Using EasyOCR2](text_and_code_reading/easyocr2/using_easyocr2.html.md): How to detect, set a topology for, learn, and recognize characters with EasyOCR2, including classifier choice and GPU acceleration.
- [Advanced Parameters](text_and_code_reading/easyocr2/setting_the_parameters.html.md): Reference for EasyOCR2's advanced segmentation, detection, and no-topology parameters controlling character isolation and text box fitting.
- [EasyMatrixCode - Reading Matrix Codes](text_and_code_reading/easymatrixcode2/index.html.md): Introduces EasyMatrixCode2, eVision's data matrix code reader, covering grid reading and ISO/SEMI grading, with links to specs and usage.
- [Specifications and Supported Symbols](text_and_code_reading/easymatrixcode2/specifications.html.md): Defines the data matrix code structure and lists the ECC000-ECC140, ECC200, and DMRE symbol sizes and capacities supported by EasyMatrixCode2.
- [Using EasyMatrixCode](text_and_code_reading/easymatrixcode2/using_easymatrixcode2.html.md): Details EasyMatrixCode2 usage: read parameters, GS1 decoding, print quality grading, model learning, grid reading, and asynchronous processing.
- [EasyMatrixCode1 - Reading Matrix Codes (deprecated)](text_and_code_reading/easymatrixcode2/easymatrixcode/index.html.md): Documents the deprecated EasyMatrixCode data matrix reader library and explains why to migrate to EasyMatrixCode2 instead.
- [Specifications](text_and_code_reading/easymatrixcode2/easymatrixcode/specifications.html.md): Defines the data matrix code structure and the size, contrast, and quiet-zone specifications supported by the deprecated EasyMatrixCode library.
- [Supported Symbols](text_and_code_reading/easymatrixcode2/easymatrixcode/supported_symbols.html.md): Lists the ECC000-ECC140 and ECC200 data matrix symbol sizes, capacities, and error correction rates supported by the deprecated EasyMatrixCode library.
- [Workflow](text_and_code_reading/easymatrixcode2/easymatrixcode/workflow.html.md): This library is deprecated, use **EasyMatrixCode2** instead.
- [Learning a Matrix Code](text_and_code_reading/easymatrixcode2/easymatrixcode/learning_a_matrix_code.html.md): How to learn a data matrix code model with the deprecated EasyMatrixCode reader to speed up and restrict subsequent code reads.
- [Computing the Print Quality](text_and_code_reading/easymatrixcode2/easymatrixcode/computing_the_print_quality.html.md): How to compute BC11, ISO 15415, ISO 29158, and SEMI T10-0701 print quality grades with the deprecated EasyMatrixCode library.
- [Using GS1 Data Matrix Codes](text_and_code_reading/easymatrixcode2/easymatrixcode/using_gs1_data_matrix_codes.html.md): Explains how to interpret GS1-compliant data matrix code contents read by the deprecated EasyMatrixCode library.
- [EasyQRCode - Reading QR Codes](text_and_code_reading/easyqrcode/index.html.md): Introduces EasyQRCode, eVision's QR code reader library, covering automatic reading, grid support, and ISO grading, with links to specs and usage.
- [Specifications](text_and_code_reading/easyqrcode/specifications.html.md): Defines QR code structure, models, versions, error correction levels, and the detection specifications supported by EasyQRCode.
- [Using EasyQRCode](text_and_code_reading/easyqrcode/using_easyqrcode.html.md): Details EasyQRCode usage: EQRCode contents, geometry, decoding GS1 and byte data, print quality grading, grid reading, and advanced detection parameters.
- [ECodeReader - Unified Interface](text_and_code_reading/ecodereader.html.md): Introduces ECodeReader, eVision's unified interface for reading bar codes, data matrix codes, and QR codes in a single operation.
- [List of Supported Codes](text_and_code_reading/list_of_supported_codes.html.md): Reference table of all bar code, mail bar code, data matrix code, and QR code symbologies supported by eVision's code reading libraries.
- [Code Grading](text_and_code_reading/code_grading/index.html.md): Introduces eVision's code grading standards for bar codes, data matrix, and QR codes, and how to compute grades with the code reader classes.
- [ISO/IEC 15416 for 1D Bar Codes](text_and_code_reading/code_grading/iso-iec_15416_for_1d_bar_codes.html.md): Explains the ISO/IEC 15416 print quality standard and its scan-line-based grading indicators for 1D bar codes as implemented in eVision.
- [ISO/IEC 15415 for Data Matrix and QR Codes](text_and_code_reading/code_grading/iso-iec_15415_for_data_matrix_and_qr_codes.html.md): Explains the ISO/IEC 15415 print quality standard and its grading indicators for data matrix and QR code symbols as implemented in eVision.
- [ISO/IEC 29158 for Data Matrix and QR Codes](text_and_code_reading/code_grading/iso-iec_29158_for_data_matrix_and_qr_codes.html.md): Explains the ISO/IEC 29158 DPM grading standard, its calibration procedure, and quality indicators for data matrix and QR codes in eVision.
- [SEMI T10-0701 for Data Matrix Codes](text_and_code_reading/code_grading/semi_t10-0701_for_data_matrix_codes.html.md): Explains the SEMI T10-0701 pixel-based grading standard and its quality indicators for direct part mark data matrix codes in eVision.
- [Comparison of OCR methods](text_and_code_reading/comparison_of_ocr_methods.html.md): Compares EasyOCR2 against the legacy EasyOCR library, covering rotation handling, dotted characters, illumination, and pretrained classifiers.
- [Deep Learning Inspection](deep_learning/index.html.md): Overview of eVision's deep learning inspection tools, EasyClassify, EasySegment, and EasyLocate, with links to Deep Learning Studio and hardware support.
- [Deep Learning Studio](deep_learning/deep_learning_studio.html.md): Introduces Deep Learning Studio, the GUI application for creating datasets, training, and evaluating eVision deep learning tools.
- [Workflow](deep_learning/easydeeplearning/index.html.md): Overview of the Deep Learning Studio workflow, from choosing a tool and annotating a dataset to training, inference, and benchmarking.
- [Choose Your Tool](deep_learning/easydeeplearning/choose_your_tool.html.md): Compares EasyClassify, EasySegment, and EasyLocate to help you choose the right deep learning tool for your application.
- [Managing the Dataset and the Annotations](deep_learning/easydeeplearning/managing_the_dataset_and_the_annotations.html.md): Explains how to add images to a dataset and annotate them with labels, segmentation, or objects for eVision deep learning tools.
- [Managing the Dataset Splits](deep_learning/easydeeplearning/managing_the_dataset_splits.html.md): Explains why and how to split a dataset into training, validation, and test sets to reliably evaluate a deep learning tool.
- [Using Data Augmentation](deep_learning/easydeeplearning/using_data_augmentation.html.md): Describes the geometric, color, and noise transformations available for data augmentation when training a deep learning tool.
- [Training a Deep Learning Tool](deep_learning/easydeeplearning/training_a_deep_learning_tool.html.md): Explains how to train a deep learning tool, covering iterations, batch size, deterministic training, and asynchronous execution.
- [Using a Deep Learning Tool](deep_learning/easydeeplearning/using_a_deep_learning_tool.html.md): Explains how to apply a trained deep learning tool to new images in Deep Learning Studio and through the API.
- [Benchmarking a Deep Learning Tool](deep_learning/easydeeplearning/benchmarking_a_deep_learning_tool.html.md): Explains how to benchmark a trained deep learning tool in Deep Learning Studio to measure throughput and latency under different execution settings.
- [Execution Settings and Hardware Support (CPU/GPU)](deep_learning/engines_and_hardware_support_cpu-gpu.html.md): Describes the CPU and GPU execution engines for eVision deep learning tools, including OpenVINO, TensorRT, multi-GPU use, and memory settings.
- [EasyClassify - Multi-label Image Classification](deep_learning/easyclassify/index.html.md): Guide to EasyClassify, the deep learning image classifier, covering capacity, image format, pretrained models, heatmaps, training, and inference.
- [EasySegment - Detecting and Segmenting Defects](deep_learning/easysegment/index.html.md): Overview of EasySegment's supervised and unsupervised defect segmentation modes and when to use each.
- [EasySegment Unsupervised](deep_learning/easysegment/easysegment_unsupervised.html.md): Guide to EasySegment Unsupervised, which trains only on good images to detect unexpected defects, covering properties and metrics.
- [EasySegment Supervised](deep_learning/easysegment/easysegment_supervised.html.md): Guide to EasySegment Supervised, which learns from ground truth segmentation maps to detect and segment defects, covering properties and metrics.
- [EasyLocate - Locating Objects and Defects](deep_learning/easylocate/index.html.md): Guide to EasyLocate, the deep learning tool for locating objects with bounding boxes or interest points, covering properties, training, and validation.
- [3D Processing](3d_processing/index.html.md): Overview of the 3D Processing libraries Easy3D, Easy3DLaserLine, Easy3DObject, and Easy3DMatch, with links to their guides and reference manuals.
- [Easy3D - Tools for 3D Object Processing](3d_processing/easy3d/index.html.md): Introduces Easy3D's 3D representation and containers, including E3DPoint, E3DLine, E3DPlane, E3DSphere, E3DBox, and E3DObject.
- [Depth Map](3d_processing/easy3d/depth_map.html.md): Introduces the depth map representation, a grayscale image encoding 3D displacement per pixel, used as the raw output of a laser triangulation scan.
- [Point Cloud](3d_processing/easy3d/point_cloud.html.md): Covers point cloud attributes, normals, transformations, cropping, decimation, plane and sphere fitting, and alignment with Easy3D.
- [Mesh](3d_processing/easy3d/mesh.html.md): Describes the EMesh triangle mesh representation and how to generate a mesh from a depth map, a ZMap, or a point cloud.
- [ZMap](3d_processing/easy3d/zmap.html.md): Explains ZMaps, the grayscale representation of a metric 3D surface projected onto a reference plane, including generation, coordinates, and leveling.
- [3D Filters and Statistics](3d_processing/easy3d/3d_filters_and_statistics.html.md): Explains the EFilters and EStatistics classes for removing noise and computing local statistics on ZMaps and depth maps.
- [3D Viewer](3d_processing/easy3d/3d_viewer.html.md): Describes the E3DViewer interactive 3D viewer for point clouds, ZMaps, and meshes, covering render sources, shading, color ramps, and point picking.
- [Photometric Stereo](3d_processing/easy3d/photometric_stereo.html.md): Explains photometric stereo, a technique that estimates surface normals and albedo from several images taken under different light directions.
- [Easy3DLaserLine - Laser Line Extraction and Calibration](3d_processing/easy3dlaserline.html.md): Guide to Easy3DLaserLine, covering laser line extraction methods, hardware versus software performance, and object-based calibration of a triangulation setup.
- [Easy3DObject - Extracting 3D Objects](3d_processing/easy3dobject.html.md): Guide to Easy3DObject, covering how the E3DObjectExtractor detects objects on a ZMap and computes features like height, area, and volume.
- [Easy3DMatch - 3D Alignment and Comparison](3d_processing/easy3dmatch.html.md): Guide to Easy3DMatch, covering alignment, comparison, anomaly detection, and multi-sensor point cloud fusion for scanned 3D objects.
- [Applicative Processing](applicative_processing/index.html.md): Overview of eVision's applicative processing tools, currently featuring EasySpotDetector for surface inspection in battery, film, and glass industries.
- [Easy Spot Detector - Detecting Spots with Deep Learning](applicative_processing/easyspotdetector.html.md): Explains the deprecated EasySpotDetector tool for detecting particles and scratches on surfaces, with optional deep learning classification.
- [Live Image Acquisition](live_image_acquisition/index.html.md): Overview of eVision's live image acquisition capabilities using the EGrabberBridge and VimbaXBridge image acquisition bridges.
- [EGrabberBridge - Using Images from eGrabber Sources](live_image_acquisition/egrabberbridge.html.md): Explains EGrabberBridge, which converts image buffers from Coaxlink and Gigelink eGrabber sources directly into eVision data containers.
- [VimbaXBridge - Using Images from VimbaX Sources](live_image_acquisition/vimbaxbridge.html.md): Explains VimbaXBridge, which converts image buffers from Allied Vision VimbaX cameras directly into eVision data containers.
- [Advanced Operations](advanced_operations/index.html.md): Overview of eVision's advanced operations: camera calibration and multicore processing.
- [Camera Calibration](advanced_operations/camera_calibration/index.html.md): Explains the purpose of eVision's camera calibration API: mapping real-world coordinates to image sensor coordinates and back.
- [Calibration Modes and Models](advanced_operations/camera_calibration/calibration_modes_and_models.html.md): Describes eVision's camera calibration models and modes, including field-of-view, advanced, and empirical calibration, and their parameters.
- [Computing the Calibration Model](advanced_operations/camera_calibration/computing_the_calibration_model.html.md): Explains how to compute an eVision camera calibration model manually, via automatic dot grid calibration, or using landmark points.
- [Unwarping an Image](advanced_operations/camera_calibration/unwarping_an_image.html.md): Explains how to unwarp an image in eVision using a computed camera calibration model to produce a rectified, distortion-free image.
- [Multicore Processing](advanced_operations/multicore_processing.html.md): Describes how to enable multicore processing in eVision and the thread-safety rules for images, ROIs, gauges, and other tool classes.

## Optional

- [Top-level llms.txt](../llms.txt): Complete documentation index.