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diff --git a/ml/dlib/docs/docs/imaging.xml b/ml/dlib/docs/docs/imaging.xml new file mode 100644 index 000000000..2fef49e73 --- /dev/null +++ b/ml/dlib/docs/docs/imaging.xml @@ -0,0 +1,2608 @@ +<?xml version="1.0" encoding="ISO-8859-1"?> +<?xml-stylesheet type="text/xsl" href="stylesheet.xsl"?> + +<doc> + <title>Image Processing</title> + + <!-- ************************************************************************* --> + + <body> + + <p> + This page documents the functionality present in this library that deals with the + management and manipulation of images. One thing to note is that there is no + explicit image object. Instead, everything deals with <a href="containers.html#array2d"> + array2d</a> objects that contain various kinds of pixels or user defined <a href="dlib/image_processing/generic_image.h.html"> + generic image</a> objects. + </p> + + + <p> + <h2>Pixel Types</h2> + Most image handling routines in dlib will accept images containing any pixel type. + This is made possible by defining a traits class, <a href="#pixel_traits">pixel_traits</a>, for + each possible pixel type. This traits class enables image processing routines to determine + how to handle each kind of pixel and therefore only pixels which have a pixel_traits definition + may be used. The following list defines all the pixel types which come with pixel_traits definitions. + <ul> + <li><b>RGB</b> + <ul> There are two RGB pixel types in dlib, <a href="#rgb_pixel">rgb_pixel</a> and <a href="#bgr_pixel">bgr_pixel</a>. + Each defines a 24bit RGB pixel type. The bgr_pixel is identical to rgb_pixel except that it lays + the color channels down in memory in BGR order rather than RGB order and is therefore useful + for interfacing with other image processing tools which expect this format (e.g. <a href="#cv_image">OpenCV</a>). </ul> + </li> + <li><b>RGB Alpha</b> + <ul>The <a href="#rgb_alpha_pixel">rgb_alpha_pixel</a> is an 8bit per channel RGB pixel with an 8bit alpha channel.</ul> + </li> + <li><b>HSI</b> + <ul>The <a href="#hsi_pixel">hsi_pixel</a> is a 24bit pixel which represents a point in the Hue Saturation Intensity + (HSI) color space. </ul> + </li> + <li><b>LAB</b> + <ul>The <a href="#lab_pixel">lab_pixel</a> is a 24bit pixel which represents a point in the CIELab color space. </ul> + </li> + <li><b>Grayscale</b> + <ul>Any built in scalar type may be used as a grayscale pixel type. For example, unsigned char, int, double, etc.</ul> + </li> + </ul> + </p> + + <p> + <h2>Object Detection</h2> + If you want to create object detectors then try the + <a href="#scan_fhog_pyramid">scan_fhog_pyramid</a> tool first. It is quite + easy to use and train and will, in many cases, give excellent results. If that + doesn't give good results then try the more powerful + <a href="ml.html#loss_mmod_">convolutional neural network</a> based detector. + </p> + + </body> + + <!-- ************************************************************************* --> + + <menu width="150"> + <top> + + <section> + <name>Pixels</name> + <item>rgb_pixel</item> + <item>bgr_pixel</item> + <item>rgb_alpha_pixel</item> + <item>hsi_pixel</item> + <item>lab_pixel</item> + <item>pixel_traits</item> + <item>get_pixel_intensity</item> + <item>assign_pixel</item> + <item>assign_pixel_intensity</item> + </section> + + <section> + <name>Image I/O</name> + <item>jpeg_loader</item> + <item>load_bmp</item> + <item>load_dng</item> + <item>load_image</item> + <item>load_jpeg</item> + <item>load_png</item> + <item>png_loader</item> + <item>save_bmp</item> + <item>save_dng</item> + <item>save_png</item> + <item>save_jpeg</item> + </section> + + <section> + <name>Object Detection</name> + <item>get_frontal_face_detector</item> + <item>object_detector</item> + <item>evaluate_detectors</item> + <item>full_object_detection</item> + <item>mmod_rect</item> + <item>scan_image</item> + <item>scan_image_movable_parts</item> + <item>find_points_above_thresh</item> + <item>scan_image_pyramid</item> + <item>scan_image_boxes</item> + <item>scan_fhog_pyramid</item> + <item>scan_image_custom</item> + <item>find_candidate_object_locations</item> + <item>test_box_overlap</item> + <item>remove_unobtainable_rectangles</item> + <item>setup_hashed_features</item> + <item>correlation_tracker</item> + <item nolink="true"> + <name>Scan Image Pyramid Tools</name> + <sub> + <item>compute_box_dimensions</item> + <item>create_single_box_detection_template</item> + <item>create_overlapped_2x2_detection_template</item> + <item>create_grid_detection_template</item> + + <item>determine_object_boxes</item> + <item>setup_grid_detection_templates</item> + <item>setup_grid_detection_templates_verbose</item> + </sub> + </item> + </section> + + <section> + <name>Feature Extraction</name> + <item>get_surf_points</item> + <item>shape_predictor</item> + <item nolink="true"> + <name>SURF Tools</name> + <sub> + <item>hessian_pyramid</item> + <item>compute_surf_descriptor</item> + <item>haar_x</item> + <item>haar_y</item> + <item>get_interest_points</item> + <item>interest_point</item> + <item>surf_point</item> + <item>compute_dominant_angle</item> + <item>draw_surf_points</item> + </sub> + </item> + + <item>hog_image</item> + <item>extract_fhog_features</item> + <item>fine_hog_image</item> + <item>poly_image</item> + <item>hashed_feature_image</item> + <item>binned_vector_feature_image</item> + <item>nearest_neighbor_feature_image</item> + <item>randomly_sample_image_features</item> + + <item>make_uniform_lbp_image</item> + <item>extract_histogram_descriptors</item> + <item>extract_uniform_lbp_descriptors</item> + <item>extract_highdim_face_lbp_descriptors</item> + </section> + + + <section> + <name>Edges and Thresholds</name> + <item>edge_orientation</item> + <item>hysteresis_threshold</item> + <item>sobel_edge_detector</item> + <item>suppress_non_maximum_edges</item> + <item>threshold_image</item> + <item>auto_threshold_image</item> + <item>hough_transform</item> + </section> + + <section> + <name>Morphology</name> + <item>label_connected_blobs</item> + <item>segment_image</item> + <item>binary_dilation</item> + <item>binary_erosion</item> + <item>binary_open</item> + <item>binary_close</item> + <item>binary_intersection</item> + <item>binary_union</item> + <item>binary_difference</item> + <item>binary_complement</item> + <item>skeleton</item> + </section> + + <section> + <name>Filtering</name> + <item>gaussian_blur</item> + <item>spatially_filter_image</item> + <item>spatially_filter_image_separable</item> + <item>float_spatially_filter_image_separable</item> + <item>separable_3x3_filter_block_grayscale</item> + <item>separable_3x3_filter_block_rgb</item> + <item>sum_filter</item> + <item>sum_filter_assign</item> + <item>max_filter</item> + <item>spatially_filter_image_separable_down</item> + </section> + + <section> + <name>Scaling and Rotating</name> + <item>pyramid_up</item> + <item>pyramid_down</item> + <item>pyramid_disable</item> + <item>create_tiled_pyramid</item> + + <item>interpolate_nearest_neighbor</item> + <item>interpolate_bilinear</item> + <item>interpolate_quadratic</item> + <item>transform_image</item> + <item>rotate_image</item> + <item>resize_image</item> + <item>flip_image_left_right</item> + <item>flip_image_up_down</item> + <item>add_image_left_right_flips</item> + <item>add_image_rotations</item> + <item>upsample_image_dataset</item> + <item>flip_image_dataset_left_right</item> + <item>rotate_image_dataset</item> + <item>extract_image_chips</item> + <item>random_cropper</item> + <item>jitter_image</item> + <item>sub_image</item> + </section> + + <section> + <name>Visualization</name> + <item>randomly_color_image</item> + <item>heatmap</item> + <item>jet</item> + <item>render_face_detections</item> + <item>draw_line</item> + <item>draw_solid_circle</item> + <item>draw_surf_points</item> + <item>draw_rectangle</item> + <item>tile_images</item> + <item>draw_fhog</item> + <item>fill_rect</item> + </section> + + <section> + <name>Miscellaneous</name> + <item>cv_image</item> + <item>toMat</item> + <item>assign_image</item> + <item>assign_image_scaled</item> + <item>assign_all_pixels</item> + <item>assign_border_pixels</item> + <item>equalize_histogram</item> + <item>get_histogram</item> + <item>zero_border_pixels</item> + <item>integral_image</item> + <item>integral_image_generic</item> + <item>disturb_colors</item> + <item>random_color_transform</item> + + </section> + + </top> + </menu> + + <!-- ************************************************************************* --> + <!-- ************************************************************************* --> + <!-- ************************************************************************* --> + + <components> + + <!-- ************************************************************************* --> + + <component> + <name>hough_transform</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/hough_transform_abstract.h</spec_file> + <description> + This object is a tool for computing the line finding version of + the Hough transform given some kind of edge detection image as + input. It also allows the edge pixels to be weighted such that + higher weighted edge pixels contribute correspondingly more to + the output of the Hough transform, allowing stronger edges to + create correspondingly stronger line detections in the final + Hough transform. + </description> + <examples> + <example>hough_transform_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>skeleton</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This function computes the skeletonization of an image. That is, + given a binary image, we progressively thin the binary blobs + until only a single pixel wide skeleton of the original blobs + remains. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>disturb_colors</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/random_color_transform_abstract.h</spec_file> + <description> + Applies a random color transform an image. This is done by + creating a <a href="#random_color_transform">random_color_transform</a> with the given parameters and then + transforming each pixel in the image with the resulting transform. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>random_color_transform</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/random_color_transform_abstract.h</spec_file> + <description> + This object generates a random color balancing and gamma correction + transform. It then allows you to apply that specific transform to as many + <a href="#rgb_pixel">rgb_pixel</a> objects as you like. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>integral_image_generic</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/integral_image_abstract.h</spec_file> + <description> + This object is an alternate way of representing image data + that allows for very fast computations of sums of pixels in + rectangular regions. To use this object you load it with a + normal image and then you can use the get_sum_of_area() + member function to compute sums of pixels in a given area in + constant time. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>integral_image</name> + <file>dlib/image_transforms.h</file> + <spec_file>dlib/image_transforms/integral_image_abstract.h</spec_file> + <description> + This is a specialization of the <a href="#integral_image_generic">integral_image_generic</a> + template for the case where sums of pixel values should be represented with + longs. E.g. if you use 8bit pixels in your original images then this is + the appropriate kind of integral image to use with them. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>haar_x</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/integral_image_abstract.h</spec_file> + <description> + This is a function that operates on an <a href="#integral_image">integral_image</a> + and allows you to compute the response of a Haar wavelet oriented along + the X axis. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>haar_y</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/integral_image_abstract.h</spec_file> + <description> + This is a function that operates on an <a href="#integral_image">integral_image</a> + and allows you to compute the response of a Haar wavelet oriented along + the Y axis. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>draw_surf_points</name> + <file>dlib/image_keypoint/draw_surf_points.h</file> + <spec_file link="true">dlib/image_keypoint/draw_surf_points_abstract.h</spec_file> + <description> + This routine adds a bunch of <a href="#surf_point">surf_point</a> objects onto + an <a href="dlib/gui_widgets/widgets_abstract.h.html#image_window">image_window</a> + object so they can be visualized. + </description> + <examples> + <example>surf_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>compute_dominant_angle</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/surf_abstract.h</spec_file> + <description> + Computes and returns the dominant angle (i.e. the angle of the dominant gradient) + at a given point and scale in an image. This function is part of the + main processing of the SURF algorithm. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>get_surf_points</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/surf_abstract.h</spec_file> + <description> + This function runs the complete SURF algorithm on an input image and + returns the points it found. For a description of what exactly + the SURF algorithm does you should read the following paper: + <blockquote> + SURF: Speeded Up Robust Features + By Herbert Bay, Tinne Tuytelaars, and Luc Van Gool + </blockquote> + <p> + Also note that there are numerous flavors of the SURF algorithm + you can put together using the functions in dlib. The get_surf_points() + function is just an example of one way you might do so. + </p> + </description> + <examples> + <example>surf_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>shape_predictor</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/shape_predictor_abstract.h</spec_file> + <description> + This object is a tool that takes in an image region containing some object + and outputs a set of point locations that define the pose of the + object. The classic example of this is human face pose prediction, where + you take an image of a human face as input and are expected to identify the + locations of important facial landmarks such as the corners of the mouth + and eyes, tip of the nose, and so forth. For example, here is the output + of dlib's <a href="face_landmark_detection_ex.cpp.html">68-face-landmark shape_predictor</a> on an image from the HELEN dataset: <br/><br/> + + <img src='face_landmarking_example.png'/> + <br/><br/> + + To create useful instantiations of this object you need to use the + <a href="ml.html#shape_predictor_trainer">shape_predictor_trainer</a> object to train a + shape_predictor using a set of training images, each annotated with shapes you want to predict. + To do this, the shape_predictor_trainer uses the state-of-the-art method from the + paper: + <blockquote> + One Millisecond Face Alignment with an Ensemble of Regression Trees + by Vahid Kazemi and Josephine Sullivan, CVPR 2014 + </blockquote> + </description> + <examples> + <example>face_landmark_detection_ex.cpp.html</example> + <example>train_shape_predictor_ex.cpp.html</example> + <example>webcam_face_pose_ex.cpp.html</example> + + <example>train_shape_predictor.py.html</example> + <example>face_landmark_detection.py.html</example> + <example>face_alignment.py.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>compute_surf_descriptor</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/surf_abstract.h</spec_file> + <description> + Computes the 64 dimensional SURF descriptor vector of a box centered + at a given center point, tilted at a given angle, and sized according to + a given scale. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>hog_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/hog_abstract.h</spec_file> + <description> + This object is a tool for performing the image feature extraction algorithm + described in the following paper: + <blockquote> + Histograms of Oriented Gradients for Human Detection + by Navneet Dalal and Bill Triggs + </blockquote> + </description> + <examples> + <example>object_detector_ex.cpp.html</example> + <example>train_object_detector.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>extract_fhog_features</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/fhog_abstract.h</spec_file> + <description> + This function implements the HOG feature extraction method described in + the paper: + <blockquote> + Object Detection with Discriminatively Trained Part Based Models by + P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan + in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, Sep. 2010 + </blockquote> + This means that it takes an input image and outputs Felzenszwalb's + 31 dimensional version of HOG features. + </description> + <examples> + <example>fhog_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>fine_hog_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/fine_hog_image_abstract.h</spec_file> + <description> + This object is a version of the <a href="#hog_image">hog_image</a> that + allows you to extract HOG features at a finer resolution. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>poly_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/poly_image_abstract.h</spec_file> + <description> + This object is a tool for extracting local feature descriptors from an image. + In particular, it fits polynomials to local pixel patches and + allows you to query the coefficients of these polynomials. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>hashed_feature_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/hashed_feature_image_abstract.h</spec_file> + <description> + This object is a tool for performing image feature extraction. In + particular, it wraps another image feature extractor and converts + the wrapped image feature vectors into sparse indicator vectors. It does + this by hashing each feature vector and then returns a new vector + which is zero everywhere except for the position determined by the + hash. + + <br/><br/> + The following feature extractors can be wrapped by the hashed_feature_image: + <ul style="margin-top:0em"> + <li><a href="#hog_image">hog_image</a></li> + <li><a href="#fine_hog_image">fine_hog_image</a></li> + <li><a href="#poly_image">poly_image</a></li> + </ul> + </description> + <examples> + <example>object_detector_ex.cpp.html</example> + <example>train_object_detector.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binned_vector_feature_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/binned_vector_feature_image_abstract.h</spec_file> + <description> + This object is a tool for performing image feature extraction. In + particular, it wraps another image feature extractor and converts the + wrapped image feature vectors into a high dimensional sparse vector. For + example, if the lower level feature extractor outputs the vector [3,4,5] + and this vector is hashed into the second bin of four bins then the output + sparse vector is: + <blockquote> + [0,0,0,0, 3,4,5,1, 0,0,0,0, 0,0,0,0]. + </blockquote> + That is, the output vector has a dimensionality that is equal to the number + of hash bins times the dimensionality of the lower level vector plus one. + The value in the extra dimension concatenated onto the end of the vector is + always a constant value of of 1 and serves as a bias value. This means + that, if there are N hash bins, these vectors are capable of representing N + different linear functions, each operating on the vectors that fall into + their corresponding hash bin. + + <br/><br/> + The following feature extractors can be wrapped by the binned_vector_feature_image: + <ul style="margin-top:0em"> + <li><a href="#hog_image">hog_image</a></li> + <li><a href="#fine_hog_image">fine_hog_image</a></li> + <li><a href="#poly_image">poly_image</a></li> + </ul> + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>nearest_neighbor_feature_image</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/nearest_neighbor_feature_image_abstract.h</spec_file> + <description> + This object is a tool for performing image feature extraction. In + particular, it wraps another image feature extractor and converts + the wrapped image feature vectors into sparse indicator vectors. It does + this by finding the nearest neighbor for each feature vector and returning an + indicator vector that is zero everywhere except for the position indicated by + the nearest neighbor. + + <br/><br/> + The following feature extractors can be wrapped by the nearest_neighbor_feature_image: + <ul style="margin-top:0em"> + <li><a href="#hog_image">hog_image</a></li> + <li><a href="#fine_hog_image">fine_hog_image</a></li> + <li><a href="#poly_image">poly_image</a></li> + </ul> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>hessian_pyramid</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/hessian_pyramid_abstract.h</spec_file> + <description> + This object represents an image pyramid where each level in the + pyramid holds determinants of Hessian matrices for the original + input image. This object can be used to find stable interest + points in an image. + + <br/><br/> + This object is an implementation of the fast Hessian pyramid + as described in the paper: + <blockquote> + SURF: Speeded Up Robust Features + By Herbert Bay, Tinne Tuytelaars, and Luc Van Gool + </blockquote> + + This implementation was also influenced by the very well documented + OpenSURF library and its corresponding description of how the fast + Hessian algorithm functions: + <blockquote>Notes on the OpenSURF Library by Christopher Evans</blockquote> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>get_interest_points</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/hessian_pyramid_abstract.h</spec_file> + <description> + This function extracts interest points from a <a href="#hessian_pyramid">hessian_pyramid</a>. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>interest_point</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/hessian_pyramid_abstract.h</spec_file> + <description> + This is a simple struct used to represent the interest points returned + by the <a href="#get_interest_points">get_interest_points</a> function. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>surf_point</name> + <file>dlib/image_keypoint.h</file> + <spec_file link="true">dlib/image_keypoint/surf_abstract.h</spec_file> + <description> + This is a simple struct used to represent the SURF points returned + by the <a href="#get_surf_points">get_surf_points</a> function. + </description> + <examples> + <example>surf_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>pixel_traits</name> + <file>dlib/pixel.h</file> + <spec_file>dlib/pixel.h</spec_file> + <description> + As the name implies, this is a traits class for pixel types. It allows you + to determine what sort of pixel type you are dealing with. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>hsi_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + This is a simple struct that represents a HSI colored graphical pixel. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>lab_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + This is a simple struct that represents a CIELab colored graphical pixel. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>rgb_alpha_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + This is a simple struct that represents an RGB colored graphical pixel with an + alpha channel. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>rgb_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + This is a simple struct that represents an RGB colored graphical pixel. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>bgr_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + This is a simple struct that represents a BGR colored graphical pixel. + <p> + The difference between this object and the <a href="#rgb_pixel">rgb_pixel</a> + is just that this struct lays its pixels down in memory in BGR order rather + than RGB order. You only care about this if you are doing something like + using the <a href="#cv_image">cv_image</a> object to map an OpenCV image + into a more object oriented form. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>cv_image</name> + <file>dlib/opencv.h</file> + <spec_file link="true">dlib/opencv/cv_image_abstract.h</spec_file> + <description> + This object is meant to be used as a simple wrapper around the OpenCV + IplImage struct or Mat object. Using this class template you can turn + an OpenCV image into something that looks like a normal dlib style + image object. + + <p> + So you should be able to use cv_image objects with many of the image + processing functions in dlib as well as the GUI tools for displaying + images on the screen. + </p> + + <p> + Note that you can do the reverse conversion, from dlib to OpenCV, + using the <a href="#toMat">toMat</a> routine. + </p> + </description> + <examples> + <example>webcam_face_pose_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>toMat</name> + <file>dlib/opencv.h</file> + <spec_file link="true">dlib/opencv/to_open_cv_abstract.h</spec_file> + <description> + This routine converts a dlib style image into an instance of OpenCV's cv::Mat object. + This is done by setting up the Mat object to point to the same memory as the dlib image. + <p> + Note that you can do the reverse conversion, from OpenCV to dlib, + using the <a href="#cv_image">cv_image</a> object. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>heatmap</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/colormaps_abstract.h</spec_file> + <description> + Converts a grayscale image into a heatmap. This is useful if you want + to display a grayscale image with more than 256 values. In particular, + this function uses the following color mapping: + <br/><img src="heatmap.png"/> + </description> + <examples> + <example>image_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>jet</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/colormaps_abstract.h</spec_file> + <description> + Converts a grayscale image into an image using the jet color + scheme. This is useful if you want to display a grayscale image + with more than 256 values. In particular, this function uses the + following color mapping: + <br/><img src="jet.png"/> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>randomly_color_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/colormaps_abstract.h</spec_file> + <description> + Randomly generates a mapping from gray level pixel values + to the RGB pixel space and then uses this mapping to create + a colored version an image. + <p> + This function is useful for displaying the results of some image + segmentation. For example, the output of <a href="#label_connected_blobs">label_connected_blobs</a> + or <a href="#segment_image">segment_image</a>. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>assign_pixel</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + assign_pixel() is a templated function that can assign any pixel type to another pixel type. + It will perform whatever conversion is necessary to make the assignment work. (E.g. color to + grayscale conversion) + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>assign_pixel_intensity</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + assign_pixel_intensity() is a templated function that can change the + intensity of a pixel. So if the pixel in question is a grayscale pixel + then it simply assigns that pixel the given value. However, if the + pixel is not a grayscale pixel then it converts the pixel to the + HSI color space and sets the I channel to the given intensity + and then converts this HSI value back to the original pixel's + color space. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>get_pixel_intensity</name> + <file>dlib/pixel.h</file> + <spec_file link="true">dlib/pixel.h</spec_file> + <description> + get_pixel_intensity() is a templated function that + returns the grayscale intensity of a pixel. If the pixel isn't a grayscale + pixel then it converts the pixel to grayscale and returns that value. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>png_loader</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/png_loader_abstract.h</spec_file> + <description> + This object loads a Portable Network Graphics (PNG) image file into + an <a href="containers.html#array2d">array2d</a> of <a href="dlib/pixel.h.html">pixels</a>. + <p> + Note that you must define DLIB_PNG_SUPPORT if you want to use this object. You + must also set your build environment to link to the libpng library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>jpeg_loader</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/jpeg_loader_abstract.h</spec_file> + <description> + This object loads a JPEG image file into + an <a href="containers.html#array2d">array2d</a> of <a href="dlib/pixel.h.html">pixels</a>. + <p> + Note that you must define DLIB_JPEG_SUPPORT if you want to use this object. You + must also set your build environment to link to the libjpeg library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>load_jpeg</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/jpeg_loader_abstract.h</spec_file> + <description> + This function loads a JPEG image file into + an <a href="containers.html#array2d">array2d</a> of <a href="dlib/pixel.h.html">pixels</a>. + <p> + Note that you must define DLIB_JPEG_SUPPORT if you want to use this object. You + must also set your build environment to link to the libjpeg library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>load_dng</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/image_loader_abstract.h</spec_file> + <description> + This global function loads a dlib DNG file (a lossless compressed image format) into + an <a href="containers.html#array2d">array2d</a> of <a href="dlib/pixel.h.html">pixels</a>. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>save_dng</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_saver/image_saver_abstract.h</spec_file> + <description> + This global function saves an image as a dlib DNG file (a lossless + compressed image format). + <p> + This routine can save images containing any type of pixel. However, the DNG format + can natively store only the following pixel types: <b>rgb_pixel</b>, <b>hsi_pixel</b>, + <b>rgb_alpha_pixel</b>, <b>uint8</b>, <b>uint16</b>, <b>float</b>, and <b>double</b>. + All other pixel types will be converted + into one of these types as appropriate before being saved to disk. + </p> + + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>save_png</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_saver/save_png_abstract.h</spec_file> + <description> + This global function writes an image to disk as a PNG (Portable Network Graphics) file. + <p> + Note that you must define DLIB_PNG_SUPPORT if you want to use this function. You + must also set your build environment to link to the libpng library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + <p> + This routine can save images containing any type of pixel. However, save_png() can + only natively store the following pixel types: <b>rgb_pixel</b>, + <b>rgb_alpha_pixel</b>, <b>uint8</b>, and <b>uint16</b>. All other pixel + types will be converted into one of these types as appropriate before being + saved to disk. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>save_jpeg</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_saver/save_jpeg_abstract.h</spec_file> + <description> + This global function writes an image to disk as a JPEG file. + <p> + Note that you must define DLIB_JPEG_SUPPORT if you want to use this function. You + must also set your build environment to link to the libjpeg library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + <p> + This routine can save images containing any type of pixel. However, save_jpeg() can + only natively store the following pixel types: <b>rgb_pixel</b> + and <b>uint8</b>. All other pixel types will be converted into + one of these types as appropriate before being saved to disk. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>load_image</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/load_image_abstract.h</spec_file> + <description> + This global function takes a file name, looks at its extension, and + then loads it into an <a href="containers.html#array2d">array2d</a> of + <a href="dlib/pixel.h.html">pixels</a> using the appropriate image + loading routine. The supported types are BMP, PNG, JPEG, GIF, and the dlib DNG file format. + + <p> + Note that you can only load PNG, JPEG, and GIF files if you link against + libpng, libjpeg, and libgif respectively. You will also need to #define + DLIB_PNG_SUPPORT, DLIB_JPEG_SUPPORT, and DLIB_GIF_SUPPORT. Or use CMake and + it will do all this for you. + </p> + </description> + + <examples> + <example>image_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>load_bmp</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/image_loader_abstract.h</spec_file> + <description> + This global function loads a MS Windows BMP file into an <a href="containers.html#array2d">array2d</a> of + <a href="dlib/pixel.h.html">pixels</a>. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>load_png</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_loader/png_loader_abstract.h</spec_file> + <description> + This function loads a Portable Network Graphics (PNG) image file into + an <a href="containers.html#array2d">array2d</a> of <a href="dlib/pixel.h.html">pixels</a>. + <p> + Note that you must define DLIB_PNG_SUPPORT if you want to use this object. You + must also set your build environment to link to the libpng library. However, + if you use CMake and dlib's default CMakeLists.txt file then it will get setup + automatically. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>save_bmp</name> + <file>dlib/image_io.h</file> + <spec_file link="true">dlib/image_saver/image_saver_abstract.h</spec_file> + <description> + This global function saves an image as a MS Windows BMP file. + + <p> + This routine can save images containing any type of pixel. However, it will + convert all color pixels into <b>rgb_pixel</b> and grayscale pixels into + <b>uint8</b> type before saving to disk. + </p> + + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>draw_line</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/draw_abstract.h</spec_file> + <description> + This global function draws a line on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>draw_solid_circle</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/draw_abstract.h</spec_file> + <description> + This global function draws a solid circle on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>render_face_detections</name> + <file>dlib/image_processing/render_face_detections.h</file> + <spec_file link="true">dlib/image_processing/render_face_detections_abstract.h</spec_file> + <description> + This function takes a set of <a href="#full_object_detection">full_object_detections</a> + which represent human faces annotated with 68 facial landmarks (according to the iBUG 300-W + scheme) and converts them into a form suitable for display on an + <a href="dlib/gui_widgets/widgets_abstract.h.html#image_window">image_window</a>. + + <p> + For example, it will take the output of a <a href="#shape_predictor">shape_predictor</a> + that uses this facial landmarking scheme and will produce visualizations like this: + </p> + <img src='face_landmarking_example.png'/> + + </description> + <examples> + <example>face_landmark_detection_ex.cpp.html</example> + <example>webcam_face_pose_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>draw_rectangle</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/draw_abstract.h</spec_file> + <description> + This global function draws a rectangle on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>tile_images</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/draw_abstract.h</spec_file> + <description> + This function takes an array of images and tiles them into a single large + square image and returns this new big tiled image. Therefore, it is a useful + method to visualize many small images at once. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>draw_fhog</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/fhog_abstract.h</spec_file> + <description> + This function takes a FHOG feature map which was created by + <a href="#extract_fhog_features">extract_fhog_features</a> and + converts it into an image suitable for display on the screen. In + particular, we draw all the hog cells into a grayscale image in a + way that shows the magnitude and orientation of the gradient + energy in each cell. + </description> + <examples> + <example>fhog_ex.cpp.html</example> + <example>fhog_object_detector_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>fill_rect</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/draw_abstract.h</spec_file> + <description> + This global function draws a solid rectangle on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>assign_border_pixels</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/assign_image_abstract.h</spec_file> + <description> + This global function assigns all the pixels in the border of an image to + a specific value. + </description> + + </component> + + <!-- ************************************************************************* --> + + + <component> + <name>assign_all_pixels</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/assign_image_abstract.h</spec_file> + <description> + This global function assigns all the pixels in an image a specific value. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>assign_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/assign_image_abstract.h</spec_file> + <description> + This global function copies one image into another and performs any + necessary color space conversions to make it work right. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>assign_image_scaled</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/assign_image_abstract.h</spec_file> + <description> + This global function copies one image into another and performs any + necessary color space conversions to make it work right. Additionally, + if the dynamic range of the source image is too big to fit into the destination image + then it will attempt to perform the appropriate scaling. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>get_histogram</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/equalize_histogram_abstract.h</spec_file> + <description> + This global function computes an image's histogram and returns it in the + form of a column or row <a href="linear_algebra.html#matrix">matrix</a> object. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>edge_orientation</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/edge_detector_abstract.h</spec_file> + <description> + This global function takes horizontal and vertical gradient magnitude + values and returns the orientation of the gradient. + </description> + + </component> + + + <!-- ************************************************************************* --> + + <component> + <name>equalize_histogram</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/equalize_histogram_abstract.h</spec_file> + <description> + This global function performs histogram equalization on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>hysteresis_threshold</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/thresholding_abstract.h</spec_file> + <description> + This global function performs hysteresis thresholding on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>sobel_edge_detector</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/edge_detector_abstract.h</spec_file> + <description> + This global function performs spatial filtering on an image using the + sobel edge detection filters. + </description> + + <examples> + <example>image_ex.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>suppress_non_maximum_edges</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/edge_detector_abstract.h</spec_file> + <description> + This global function performs non-maximum suppression on a gradient + image. + </description> + + <examples> + <example>image_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>zero_border_pixels</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/assign_image_abstract.h</spec_file> + <description> + This global function zeros the pixels on the border of an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>spatially_filter_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This global function performs spatial filtering on an image with a user + supplied filter. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>gaussian_blur</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This global function blurs an image by convolving it with a Gaussian filter. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>spatially_filter_image_separable</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This global function performs spatial filtering on an image with a user + supplied separable filter. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>float_spatially_filter_image_separable</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This global function performs spatial filtering on an image with a user + supplied separable filter. It is optimized to work only on float valued + images with float valued filters. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>spatially_filter_image_separable_down</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This global function performs spatial filtering on an image with a user + supplied separable filter. Additionally, it produces a downsampled + output. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>max_filter</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This function slides a rectangle over an input image and outputs a new + image which contains the maximum valued pixel found inside the rectangle at each + position in the input image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>sum_filter</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This function slides a rectangle over an input image and adds the sum + of pixel values in each rectangle location to another image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>sum_filter_assign</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This function slides a rectangle over an input image and outputs a new + image which contains the sum of pixels inside the rectangle at each + position in the input image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>separable_3x3_filter_block_grayscale</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This routine filters part of an image with a user supplied 3x3 separable filter. + The output is a grayscale sub-image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>separable_3x3_filter_block_rgb</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/spatial_filtering_abstract.h</spec_file> + <description> + This routine filters part of an image with a user supplied 3x3 separable filter. + The output is a RGB sub-image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>create_tiled_pyramid</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/image_pyramid_abstract.h</spec_file> + <description> + This function creates an image pyramid and packs the entire pyramid into + one big image. It does this by tiling the different pyramid layers together + and outputting the result. Here is an example: + <br/> + <img src='tiled_pyramid_example.jpg'/> + <br/> + + Also, you can use the + <a href="dlib/image_transforms/image_pyramid_abstract.h.html#image_to_tiled_pyramid">image_to_tiled_pyramid()</a> + and + <a href="dlib/image_transforms/image_pyramid_abstract.h.html#image_to_tiled_pyramid">tiled_pyramid_to_image()</a> routines + to convert between the input image coordinate space and the tiled pyramid + coordinate space. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>pyramid_down</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/image_pyramid_abstract.h</spec_file> + <description> + This is a simple function object to help create image pyramids. It + downsamples an image by a ratio of N to N-1 where N is supplied by the + user as a template argument. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>pyramid_disable</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/image_pyramid_abstract.h</spec_file> + <description> + This object downsamples an image at a ratio of infinity to 1. That + means it always outputs an image of size zero. This is useful because + it can be supplied to routines which take a pyramid_down function object + and it will essentially disable pyramid processing. This way, a pyramid + oriented function can be turned into a regular routine which processes + just the original undownsampled image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>interpolate_nearest_neighbor</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This object is a tool for performing nearest neighbor interpolation + on an image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>interpolate_bilinear</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This object is a tool for performing bilinear interpolation + on an image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>interpolate_quadratic</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This object is a tool for performing quadratic interpolation + on an image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>transform_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine is a tool for transforming images using some kind of point mapping + function (e.g. <a href="linear_algebra.html#point_transform_affine">point_transform_affine</a>) + and pixel interpolation tool (e.g. <a href="#interpolate_quadratic">interpolate_quadratic</a>). + An example application of this routine is for image rotation. Indeed, it is how + <a href="#rotate_image">rotate_image</a> is implemented. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>rotate_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This is a routine for rotating an image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>pyramid_up</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine upsamples an image. In particular, it takes a + <a href="#pyramid_down">pyramid_down</a> object (or an object with a + compatible interface) as an argument and performs an upsampling + which is the inverse of the supplied pyramid_down object. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>resize_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This is a routine capable of resizing or stretching an image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>extract_image_chips</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This function extracts "chips" from an image. That is, it takes a list of + rectangular sub-windows (i.e. chips) within an image and extracts those + sub-windows, storing each into its own image. It also allows the user to + specify the scale and rotation for the chip. + </description> + <examples> + <example>face_landmark_detection_ex.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>random_cropper</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/random_cropper_abstract.h</spec_file> + <description> + This object is a tool for extracting random crops of objects from a set of + images. The crops are randomly jittered in scale, translation, and + rotation but more or less centered on objects specified by <a href="#mmod_rect">mmod_rect</a> + objects. + </description> + <examples> + <example>random_cropper_ex.cpp.html</example> + <example>dnn_mmod_ex.cpp.html</example> + <example>dnn_mmod_find_cars_ex.cpp.html</example> + <example>dnn_mmod_train_find_cars_ex.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>jitter_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + Randomly jitters an image by slightly rotating, scaling, and translating it. + There is also a 50% chance it will be mirrored left to right. + </description> + <examples> + <example>dnn_metric_learning_on_images_ex.cpp.html</example> + <example>dnn_face_recognition_ex.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>sub_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This function returns a lightweight sub-image of another image. In particular, + the returned sub-image simply holds a pointer to the original image, meaning there + is no overhead for using or creating the sub-image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>add_image_left_right_flips</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine takes a set of images and bounding boxes within those + images and doubles the size of the dataset by adding left/right + flipped copies of each image as well as the corresponding bounding + boxes. Therefore, this function is useful if you are training and + object detector and your objects have a left/right symmetry. + </description> + <examples> + <example>fhog_object_detector_ex.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>add_image_rotations</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine takes a set of images and bounding boxes within those images and + grows the dataset by computing many different rotations of each image. It will + also adjust the positions of the bounding boxes so that they still fall on the + same objects in each rotated image. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>rotate_image_dataset</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine takes a set of images and bounding boxes within those + images and rotates the entire dataset by a user specified angle. + This means that all images are rotated and the bounding boxes are adjusted + so that they still sit on top of the same visual objects in the new rotated images. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>flip_image_dataset_left_right</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine takes a set of images and bounding boxes within those images and + mirrors the entire dataset left to right. This means that all images are + flipped left to right and the bounding boxes are adjusted so that they still + sit on top of the same visual objects in the new flipped images. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>upsample_image_dataset</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine takes a set of images and bounding boxes within those images and + upsamples the entire dataset. This means that all images are upsampled and the + bounding boxes are adjusted so that they still sit on top of the same visual + objects in the new images. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>flip_image_left_right</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This is a routine which can flip an image from left to right. (e.g. as + if viewed through a mirror). + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>flip_image_up_down</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/interpolation_abstract.h</spec_file> + <description> + This routine flips an image upside down. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>auto_threshold_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/thresholding_abstract.h</spec_file> + <description> + This global function performs a simple binary thresholding on an image. + Instead of taking a user supplied threshold + it computes one from the image using k-means clustering. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>threshold_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/thresholding_abstract.h</spec_file> + <description> + This global function performs a simple binary thresholding on an image with a user + supplied threshold. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>label_connected_blobs</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/label_connected_blobs_abstract.h</spec_file> + <description> + This function labels each of the connected blobs in an image with a unique integer label. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>segment_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/segment_image_abstract.h</spec_file> + <description> + Attempts to segment an image into regions which have some visual consistency to them. + In particular, this function implements the algorithm described in the paper: + <blockquote> + Efficient Graph-Based Image Segmentation by Felzenszwalb and Huttenlocher. + </blockquote> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>find_candidate_object_locations</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/segment_image_abstract.h</spec_file> + <description> + This function takes an input image and generates a set of candidate + rectangles which are expected to bound any objects in the image. It does + this by running a version of the <a href="#segment_image">segment_image</a> routine on the image and + then reports rectangles containing each of the segments as well as rectangles + containing unions of adjacent segments. The basic idea is described in the + paper: + <blockquote> + Segmentation as Selective Search for Object Recognition by Koen E. A. van de Sande, et al. + </blockquote> + Note that this function deviates from what is described in the paper slightly. + See the code for details. + </description> + <examples> + <example>find_candidate_object_locations.py.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_dilation</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function performs the morphological operation of dilation on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_erosion</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function performs the morphological operation of erosion on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_open</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function performs a morphological opening on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_close</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function performs a morphological closing on an image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_intersection</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function computes the intersection of two binary images. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_union</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function computes the union of two binary images. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_difference</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function computes the difference of two binary images. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>binary_complement</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file> + <description> + This global function computes the complement of a binary image. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_image</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_abstract.h</spec_file> + <description> + This global function is a tool for sliding a set of rectangles + over an image space and finding the locations where the sum of pixels in + the rectangles exceeds a threshold. It is useful for implementing + certain kinds of sliding window classifiers. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_image_movable_parts</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_abstract.h</spec_file> + <description> + This global function is a tool for sliding a set of rectangles + over an image space and finding the locations where the sum of pixels in + the rectangles exceeds a threshold. It is useful for implementing + certain kinds of sliding window classifiers. The behavior of this + routine is similar to <a href="#scan_image">scan_image</a> except that + it can also handle movable parts in addition to rigidly placed parts + within the sliding window. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>find_points_above_thresh</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_abstract.h</spec_file> + <description> + This routine finds all points in an image with a pixel value above a + threshold. It also has the ability to produce an efficient random + subsample of such points if the number of them is very large. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_image_pyramid</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_pyramid_abstract.h</spec_file> + <description> + This object is a tool for running a sliding window classifier over + an image pyramid. This object can also be understood as a general + tool for implementing the spatial pyramid models described in the paper: + <blockquote> + Beyond Bags of Features: Spatial Pyramid Matching for Recognizing + Natural Scene Categories by Svetlana Lazebnik, Cordelia Schmid, + and Jean Ponce + </blockquote> + It also includes the ability to represent movable part models. + + <br/><br/> + The following feature extractors can be used with the scan_image_pyramid object: + <ul style="margin-top:0em"> + <li><a href="#hashed_feature_image">hashed_feature_image</a></li> + <li><a href="#binned_vector_feature_image">binned_vector_feature_image</a></li> + <li><a href="#nearest_neighbor_feature_image">nearest_neighbor_feature_image</a></li> + </ul> + </description> + <examples> + <example>object_detector_ex.cpp.html</example> + <example>object_detector_advanced_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_fhog_pyramid</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_fhog_pyramid_abstract.h</spec_file> + <description> + + This object is a tool for running a fixed sized sliding window classifier + over an image pyramid. In particular, it slides a linear classifier over + a HOG pyramid as discussed in the paper: + <blockquote> + Histograms of Oriented Gradients for Human Detection by Navneet Dalal + and Bill Triggs, CVPR 2005 + </blockquote> + However, we augment the method slightly to use the version of HOG features + from: + <blockquote> + Object Detection with Discriminatively Trained Part Based Models by + P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan + IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, Sep. 2010 + </blockquote> + Since these HOG features have been shown to give superior performance. + </description> + <examples> + <example>fhog_object_detector_ex.cpp.html</example> + <example>train_object_detector.py.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_image_boxes</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_boxes_abstract.h</spec_file> + <description> + This object is a tool for running a classifier over an image with the goal + of localizing each object present. The localization is in the form of the + bounding box around each object of interest. + + <p> + Unlike the <a href="#scan_image_pyramid">scan_image_pyramid</a> object which scans a + fixed sized window over an image pyramid, the scan_image_boxes tool allows you to + define your own list of "candidate object locations" which should be evaluated. + This is simply a list of rectangle objects which might contain objects of + interest. The scan_image_boxes object will then evaluate the classifier at each + of these locations and return the subset of rectangles which appear to have + objects in them. + </p> + + This object can also be understood as a general tool for implementing the spatial + pyramid models described in the paper: + <blockquote> + Beyond Bags of Features: Spatial Pyramid Matching for Recognizing + Natural Scene Categories by Svetlana Lazebnik, Cordelia Schmid, + and Jean Ponce + </blockquote> + + <br/><br/> + The following feature extractors can be used with the scan_image_boxes object: + <ul style="margin-top:0em"> + <li><a href="#hashed_feature_image">hashed_feature_image</a></li> + <li><a href="#binned_vector_feature_image">binned_vector_feature_image</a></li> + <li><a href="#nearest_neighbor_feature_image">nearest_neighbor_feature_image</a></li> + </ul> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>scan_image_custom</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_custom_abstract.h</spec_file> + <description> + This object is a tool for running a classifier over an image with the goal + of localizing each object present. The localization is in the form of the + bounding box around each object of interest. + + <p> + Unlike the <a href="#scan_image_pyramid">scan_image_pyramid</a> + and <a href="#scan_image_boxes">scan_image_boxes</a> objects, this image + scanner delegates all the work of constructing the object feature vector to + a user supplied feature extraction object. That is, scan_image_custom + simply asks the supplied feature extractor what boxes in the image we + should investigate and then asks the feature extractor for the complete + feature vector for each box. That is, scan_image_custom does not apply any + kind of pyramiding or other higher level processing to the features coming + out of the feature extractor. That means that when you use + scan_image_custom it is completely up to you to define the feature vector + used with each image box. + </p> + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>full_object_detection</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/full_object_detection_abstract.h</spec_file> + <description> + This object represents the location of an object in an image along with the + positions of each of its constituent parts. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>mmod_rect</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/full_object_detection_abstract.h</spec_file> + <description> + This is a simple struct that is used to give training data and receive detections + from the <a href="ml.html#loss_mmod_">Max-Margin Object Detection loss layer</a>. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>get_frontal_face_detector</name> + <file>dlib/image_processing/frontal_face_detector.h</file> + <spec_file link="true">dlib/image_processing/frontal_face_detector_abstract.h</spec_file> + <description> + This function returns an <a href="#object_detector">object_detector</a> that is + configured to find human faces that are looking more or less towards the camera. + It is created using the <a href="#scan_fhog_pyramid">scan_fhog_pyramid</a> + object. + </description> + <examples> + <example>face_detection_ex.cpp.html</example> + <example>face_detector.py.html</example> + <example>webcam_face_pose_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>object_detector</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/object_detector_abstract.h</spec_file> + <description> + This object is a tool for detecting the positions of objects in an image. In + particular, it is a simple container to aggregate an instance of an image + scanner object (either <a href="#scan_fhog_pyramid">scan_fhog_pyramid</a>, + <a href="#scan_image_pyramid">scan_image_pyramid</a>, <a + href="#scan_image_boxes">scan_image_boxes</a>, or + <a href="#scan_image_custom">scan_image_custom</a>), the weight vector + needed by one of these image scanners, and finally an instance of + <a href="#test_box_overlap">test_box_overlap</a>. The test_box_overlap object + is used to perform non-max suppression on the output of the image scanner + object. + + <p> + Note that you can use the + <a href="ml.html#structural_object_detection_trainer">structural_object_detection_trainer</a> + to learn the parameters of an object_detector. See the example programs for an introduction. + </p> + + <p> + Also note that dlib contains more powerful <a + href="ml.html#loss_mmod_">CNN based object detection + tooling</a>, which will usually run slower but produce much + more general and accurate detectors. + </p> + + </description> + <examples> + <example>fhog_object_detector_ex.cpp.html</example> + <example>face_detection_ex.cpp.html</example> + <example>object_detector_ex.cpp.html</example> + <example>object_detector_advanced_ex.cpp.html</example> + <example>train_object_detector.cpp.html</example> + + <example>face_detector.py.html</example> + <example>train_object_detector.py.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>correlation_tracker</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/correlation_tracker_abstract.h</spec_file> + <description> + This is a tool for tracking moving objects in a video stream. You give it + the bounding box of an object in the first frame and it attempts to track the + object in the box from frame to frame. + + <p> + This tool is an implementation of the method described in the following paper: + <blockquote> + Danelljan, Martin, et al. "Accurate scale estimation for robust visual + tracking." Proceedings of the British Machine Vision Conference BMVC. 2014. + </blockquote> + </p> + </description> + <examples> + <example>video_tracking_ex.cpp.html</example> + <example>correlation_tracker.py.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>evaluate_detectors</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_fhog_pyramid_abstract.h</spec_file> + <description> + This function allows you to efficiently run a bunch of + <a href="#scan_fhog_pyramid">scan_fhog_pyramid</a> based + <a href="#object_detector">object_detectors</a> + over an image. Importantly, this function is faster than running + each detector individually because it computes the HOG features + only once and then reuses them for each detector. + </description> + <examples> + <example>fhog_object_detector_ex.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>test_box_overlap</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/box_overlap_testing_abstract.h</spec_file> + <description> + This object is a simple function object for determining if two + <a href="linear_algebra.html#rectangle">rectangles</a> overlap. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>remove_unobtainable_rectangles</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/remove_unobtainable_rectangles_abstract.h</spec_file> + <description> + Recall that the <a href="#scan_image_pyramid">scan_image_pyramid</a> and + <a href="#scan_image_boxes">scan_image_boxes</a> objects can't produce + all possible rectangles as object detections since they only + consider a limited subset of all possible object positions. + Therefore, when training an object detector that uses these tools + you must make sure the training data does not contain any object + locations that are unobtainable by the image scanning model. + The remove_unobtainable_rectangles() routine is a tool to filter out + these unobtainable rectangles from the training. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>compute_box_dimensions</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/detection_template_tools_abstract.h</spec_file> + <description> + This function is a tool for computing a rectangle with a particular + width/height ratio and area. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>create_single_box_detection_template</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/detection_template_tools_abstract.h</spec_file> + <description> + This function is a tool for creating a detection template usable by + the <a href="#scan_image_pyramid">scan_image_pyramid</a> object. This + particular function creates a detection template with exactly one feature + extraction region. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>create_overlapped_2x2_detection_template</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/detection_template_tools_abstract.h</spec_file> + <description> + This function is a tool for creating a detection template usable by + the <a href="#scan_image_pyramid">scan_image_pyramid</a> object. This + particular function creates a detection template with four overlapping feature + extraction regions. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>create_grid_detection_template</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/detection_template_tools_abstract.h</spec_file> + <description> + This function is a tool for creating a detection template usable by + the <a href="#scan_image_pyramid">scan_image_pyramid</a> object. This + particular function creates a detection template with a grid of feature + extraction regions. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>determine_object_boxes</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_pyramid_tools_abstract.h</spec_file> + <description> + The <a href="#scan_image_pyramid">scan_image_pyramid</a> object represents a sliding + window classifier system. For it to work correctly it needs to be given a set of + object boxes which define the size and shape of each sliding window and these windows + need to be able to match the sizes and shapes of targets the user wishes to detect. + Therefore, the determine_object_boxes() routine is a tool for computing a set of object boxes + which can meet this requirement. + + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>setup_grid_detection_templates</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_pyramid_tools_abstract.h</spec_file> + <description> + This routine uses <a href="#determine_object_boxes">determine_object_boxes</a> to obtain a set of + object boxes and then adds them to a <a href="#scan_image_pyramid">scan_image_pyramid</a> object + as detection templates. It also uses <a href="#create_grid_detection_template">create_grid_detection_template</a> + to create each feature extraction region. Therefore, the detection templates will extract + features from a regular grid inside each object box. + </description> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>setup_grid_detection_templates_verbose</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/scan_image_pyramid_tools_abstract.h</spec_file> + <description> + This function is identical to <a href="#setup_grid_detection_templates">setup_grid_detection_templates</a> + except that it also outputs information regarding the selected detection templates + to standard out. + </description> + <examples> + <example>object_detector_ex.cpp.html</example> + <example>train_object_detector.cpp.html</example> + </examples> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>setup_hashed_features</name> + <file>dlib/image_processing.h</file> + <spec_file link="true">dlib/image_processing/setup_hashed_features_abstract.h</spec_file> + <description> + This is a tool for configuring the <a href="#hashed_feature_image">hashed_feature_image</a> + or <a href="#binned_vector_feature_image">binned_vector_feature_image</a> object + with a random <a href="algorithms.html#projection_hash">projection hash</a>. + </description> + <examples> + <example>object_detector_ex.cpp.html</example> + <example>train_object_detector.cpp.html</example> + </examples> + + </component> + + <!-- ************************************************************************* --> + + <component> + <name>randomly_sample_image_features</name> + <file>dlib/statistics.h</file> + <spec_file link="true">dlib/statistics/image_feature_sampling_abstract.h</spec_file> + <description> + Given a feature extractor such as the <a href="#hog_image">hog_image</a>, + this routine selects a random subsample of local image feature vectors + from a set of images. + </description> + + </component> + + + <!-- ************************************************************************* --> + + <component> + <name>make_uniform_lbp_image</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file> + <description> + This function extracts the uniform local-binary-pattern feature at every pixel + of an image and stores the output in a new image object. + We use the idea of uniform LBPs from the paper: + <blockquote> + Face Description with Local Binary Patterns: Application to Face Recognition + by Ahonen, Hadid, and Pietikainen. + </blockquote> + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>extract_histogram_descriptors</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file> + <description> + This function extracts histograms of pixel values from a set of windows in an + image and returns the histograms. + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>extract_uniform_lbp_descriptors</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file> + <description> + Extracts histograms of uniform local-binary-patterns from an image. The + histograms are from densely tiled windows that do not overlap and cover all + of the image. + We use the idea of uniform LBPs from the paper: + <blockquote> + Face Description with Local Binary Patterns: Application to Face Recognition + by Ahonen, Hadid, and Pietikainen. + </blockquote> + </description> + </component> + + <!-- ************************************************************************* --> + + <component> + <name>extract_highdim_face_lbp_descriptors</name> + <file>dlib/image_transforms.h</file> + <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file> + <description> + This function extracts the high-dimensional LBP feature described in the + paper: + <blockquote> + Blessing of Dimensionality: High-dimensional Feature and Its Efficient + Compression for Face Verification by Dong Chen, Xudong Cao, Fang Wen, and + Jian Sun + </blockquote> + </description> + </component> + + <!-- ************************************************************************* --> + + </components> + + <!-- ************************************************************************* --> + + +</doc> + |