Merge pull request #96 from avdmitry/datasets

datasets module: PR for adding benchmarks and renaming module from datasetstools

modules/datasets/CMakeLists.txt

+set(the_description "datasets framework")
+ocv_define_module(datasets opencv_core opencv_face opencv_ml opencv_flann)
+
+ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4267) # flann, Win64

modules/datasets/doc/datasets.rst

+*******************************************************
+datasets. Framework for working with different datasets
+*******************************************************
+
+.. highlight:: cpp
+
+The datasets module includes classes for working with different datasets: load data, evaluate different algorithms on them, etc.
+
+.. toctree::
+    :hidden:
+
+    datasets/ar_hmdb
+    datasets/ar_sports
+    datasets/fr_lfw
+    datasets/gr_chalearn
+    datasets/gr_skig
+    datasets/hpe_parse
+    datasets/ir_affine
+    datasets/ir_robot
+    datasets/is_bsds
+    datasets/is_weizmann
+    datasets/msm_epfl
+    datasets/msm_middlebury
+    datasets/or_imagenet
+    datasets/or_mnist
+    datasets/or_sun
+    datasets/pd_caltech
+    datasets/slam_kitti
+    datasets/slam_tumindoor
+    datasets/tr_chars
+    datasets/tr_svt
+
+Action Recognition
+------------------
+
+    :doc:`datasets/ar_hmdb`
+
+    :doc:`datasets/ar_sports`
+
+Face Recognition
+----------------
+
+    :doc:`datasets/fr_lfw`
+
+Gesture Recognition
+-------------------
+
+    :doc:`datasets/gr_chalearn`
+
+    :doc:`datasets/gr_skig`
+
+Human Pose Estimation
+---------------------
+
+    :doc:`datasets/hpe_parse`
+
+Image Registration
+------------------
+
+    :doc:`datasets/ir_affine`
+
+    :doc:`datasets/ir_robot`
+
+Image Segmentation
+------------------
+
+    :doc:`datasets/is_bsds`
+
+    :doc:`datasets/is_weizmann`
+
+Multiview Stereo Matching
+-------------------------
+
+    :doc:`datasets/msm_epfl`
+
+    :doc:`datasets/msm_middlebury`
+
+Object Recognition
+------------------
+
+    :doc:`datasets/or_imagenet`
+
+    :doc:`datasets/or_mnist`
+
+    :doc:`datasets/or_sun`
+
+Pedestrian Detection
+--------------------
+
+    :doc:`datasets/pd_caltech`
+
+SLAM
+----
+
+    :doc:`datasets/slam_kitti`
+
+    :doc:`datasets/slam_tumindoor`
+
+Text Recognition
+----------------
+
+    :doc:`datasets/tr_chars`
+
+    :doc:`datasets/tr_svt`
+

modules/datasets/doc/datasets/ar_hmdb.rst

+HMDB: A Large Human Motion Database
+===================================
+.. ocv:class:: AR_hmdb
+
+Implements loading dataset:
+
+_`"HMDB: A Large Human Motion Database"`: http://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: hmdb51_org.rar & test_train_splits.rar.
+
+ 2. Unpack them.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_ar_hmdb -p=/home/user/path_to_unpacked_folders/
+
+Benchmark
+"""""""""
+
+For this dataset was implemented benchmark, which gives accuracy: 0.107407 (using precomputed HOG/HOF "STIP" features from site, averaging for 3 splits)
+
+To run this benchmark execute:
+
+.. code-block:: bash
+
+ ./opencv/build/bin/example_datasets_ar_hmdb_benchmark -p=/home/user/path_to_unpacked_folders/
+
+(precomputed features should be unpacked in the same folder: /home/user/path_to_unpacked_folders/hmdb51_org_stips/)
+

modules/datasets/doc/datasets/ar_sports.rst

+Sports-1M Dataset
+=================
+.. ocv:class:: AR_sports
+
+Implements loading dataset:
+
+_`"Sports-1M Dataset"`: http://cs.stanford.edu/people/karpathy/deepvideo/
+
+.. note:: Usage
+
+ 1. From link above download dataset files (git clone https://code.google.com/p/sports-1m-dataset/).
+
+ 2. To load data run: ./opencv/build/bin/example_datasets_ar_sports -p=/home/user/path_to_downloaded_folders/
+

modules/datasets/doc/datasets/fr_lfw.rst

+Labeled Faces in the Wild
+=========================
+.. ocv:class:: FR_lfw
+
+Implements loading dataset:
+
+_`"Labeled Faces in the Wild"`: http://vis-www.cs.umass.edu/lfw/
+
+.. note:: Usage
+
+ 1. From link above download any dataset file: lfw.tgz\lfwa.tar.gz\lfw-deepfunneled.tgz\lfw-funneled.tgz and files with pairs: 10 test splits: pairs.txt and developer train split: pairsDevTrain.txt.
+
+ 2. Unpack dataset file and place pairs.txt and pairsDevTrain.txt in created folder.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_fr_lfw -p=/home/user/path_to_unpacked_folder/lfw2/
+
+Benchmark
+"""""""""
+
+For this dataset was implemented benchmark, which gives accuracy: 0.623833 +- 0.005223 (train split: pairsDevTrain.txt, dataset: lfwa)
+
+To run this benchmark execute:
+
+.. code-block:: bash
+
+ ./opencv/build/bin/example_datasets_fr_lfw_benchmark -p=/home/user/path_to_unpacked_folder/lfw2/
+

modules/datasets/doc/datasets/gr_chalearn.rst

+ChaLearn Looking at People
+==========================
+.. ocv:class:: GR_chalearn
+
+Implements loading dataset:
+
+_`"ChaLearn Looking at People"`: http://gesture.chalearn.org/
+
+.. note:: Usage
+
+ 1. Follow instruction from site above, download files for dataset "Track 3: Gesture Recognition": Train1.zip-Train5.zip, Validation1.zip-Validation3.zip (Register on site: www.codalab.org and accept the terms and conditions of competition: https://www.codalab.org/competitions/991#learn_the_details There are three mirrors for downloading dataset files. When I downloaded data only mirror: "Universitat Oberta de Catalunya" works).
+
+ 2. Unpack train archives Train1.zip-Train5.zip to folder Train/, validation archives Validation1.zip-Validation3.zip to folder Validation/
+
+ 3. Unpack all archives in Train/ & Validation/ in the folders with the same names, for example: Sample0001.zip to Sample0001/
+
+ 4. To load data run: ./opencv/build/bin/example_datasets_gr_chalearn -p=/home/user/path_to_unpacked_folders/
+

modules/datasets/doc/datasets/gr_skig.rst

+Sheffield Kinect Gesture Dataset
+================================
+.. ocv:class:: GR_skig
+
+Implements loading dataset:
+
+_`"Sheffield Kinect Gesture Dataset"`: http://lshao.staff.shef.ac.uk/data/SheffieldKinectGesture.htm
+
+.. note:: Usage
+
+ 1. From link above download dataset files: subject1_dep.7z-subject6_dep.7z, subject1_rgb.7z-subject6_rgb.7z.
+
+ 2. Unpack them.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_gr_skig -p=/home/user/path_to_unpacked_folders/
+

modules/datasets/doc/datasets/hpe_parse.rst

+PARSE Dataset
+=============
+.. ocv:class:: HPE_parse
+
+Implements loading dataset:
+
+_`"PARSE Dataset"`: http://www.ics.uci.edu/~dramanan/papers/parse/
+
+.. note:: Usage
+
+ 1. From link above download dataset file: people.zip.
+
+ 2. Unpack it.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_hpe_parse -p=/home/user/path_to_unpacked_folder/people_all/
+

modules/datasets/doc/datasets/ir_affine.rst

+Affine Covariant Regions Datasets
+=================================
+.. ocv:class:: IR_affine
+
+Implements loading dataset:
+
+_`"Affine Covariant Regions Datasets"`: http://www.robots.ox.ac.uk/~vgg/data/data-aff.html
+
+.. note:: Usage
+
+ 1. From link above download dataset files: bark\\bikes\\boat\\graf\\leuven\\trees\\ubc\\wall.tar.gz.
+
+ 2. Unpack them.
+
+ 3. To load data, for example, for "bark", run: ./opencv/build/bin/example_datasets_ir_affine -p=/home/user/path_to_unpacked_folder/bark/
+

modules/datasets/doc/datasets/ir_robot.rst

+Robot Data Set
+==============
+.. ocv:class:: IR_robot
+
+Implements loading dataset:
+
+_`"Robot Data Set"`: http://roboimagedata.compute.dtu.dk/?page_id=24
+
+.. note:: Usage
+
+ 1. From link above download files for dataset "Point Feature Data Set – 2010": SET001_6.tar.gz-SET055_60.tar.gz (there are two data sets: - Full resolution images (1200×1600), ~500 Gb and - Half size image (600×800), ~115 Gb.)
+ 2. Unpack them to one folder.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_ir_robot -p=/home/user/path_to_unpacked_folder/
+

modules/datasets/doc/datasets/is_bsds.rst

+The Berkeley Segmentation Dataset and Benchmark
+===============================================
+.. ocv:class:: IS_bsds
+
+Implements loading dataset:
+
+_`"The Berkeley Segmentation Dataset and Benchmark"`: https://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: BSDS300-human.tgz & BSDS300-images.tgz.
+
+ 2. Unpack them.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_is_bsds -p=/home/user/path_to_unpacked_folder/BSDS300/
+

modules/datasets/doc/datasets/is_weizmann.rst

+Weizmann Segmentation Evaluation Database
+=========================================
+.. ocv:class:: IS_weizmann
+
+Implements loading dataset:
+
+_`"Weizmann Segmentation Evaluation Database"`: http://www.wisdom.weizmann.ac.il/~vision/Seg_Evaluation_DB/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: Weizmann_Seg_DB_1obj.ZIP & Weizmann_Seg_DB_2obj.ZIP.
+
+ 2. Unpack them.
+
+ 3. To load data, for example, for 1 object dataset, run: ./opencv/build/bin/example_datasets_is_weizmann -p=/home/user/path_to_unpacked_folder/1obj/
+

modules/datasets/doc/datasets/msm_epfl.rst

+EPFL Multi-View Stereo
+======================
+.. ocv:class:: MSM_epfl
+
+Implements loading dataset:
+
+_`"EPFL Multi-View Stereo"`: http://cvlabwww.epfl.ch/~strecha/multiview/denseMVS.html
+
+.. note:: Usage
+
+ 1. From link above download dataset files: castle_dense\\castle_dense_large\\castle_entry\\fountain\\herzjesu_dense\\herzjesu_dense_large_bounding\\cameras\\images\\p.tar.gz.
+
+ 2. Unpack them in separate folder for each object. For example, for "fountain", in folder fountain/ : fountain_dense_bounding.tar.gz -> bounding/, fountain_dense_cameras.tar.gz -> camera/, fountain_dense_images.tar.gz -> png/, fountain_dense_p.tar.gz -> P/
+
+ 3. To load data, for example, for "fountain", run: ./opencv/build/bin/example_datasets_msm_epfl -p=/home/user/path_to_unpacked_folder/fountain/
+

modules/datasets/doc/datasets/msm_middlebury.rst

+Stereo – Middlebury Computer Vision
+===================================
+.. ocv:class:: MSM_middlebury
+
+Implements loading dataset:
+
+_`"Stereo – Middlebury Computer Vision"`: http://vision.middlebury.edu/mview/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: dino\\dinoRing\\dinoSparseRing\\temple\\templeRing\\templeSparseRing.zip
+
+ 2. Unpack them.
+
+ 3. To load data, for example "temple" dataset, run: ./opencv/build/bin/example_datasets_msm_middlebury -p=/home/user/path_to_unpacked_folder/temple/
+

modules/datasets/doc/datasets/or_imagenet.rst

+ImageNet
+========
+.. ocv:class:: OR_imagenet
+
+Implements loading dataset:
+
+_`"ImageNet"`: http://www.image-net.org/
+
+Currently implemented loading full list with urls. Planned to implement dataset from ILSVRC challenge. 
+
+.. note:: Usage
+
+ 1. From link above download dataset file: imagenet_fall11_urls.tgz
+
+ 2. Unpack it.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_or_imagenet -p=/home/user/path_to_unpacked_file/
+

modules/datasets/doc/datasets/or_mnist.rst

+MNIST
+=====
+.. ocv:class:: OR_mnist
+
+Implements loading dataset:
+
+_`"MNIST"`: http://yann.lecun.com/exdb/mnist/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: t10k-images-idx3-ubyte.gz, t10k-labels-idx1-ubyte.gz, train-images-idx3-ubyte.gz, train-labels-idx1-ubyte.gz.
+
+ 2. Unpack them.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_or_mnist -p=/home/user/path_to_unpacked_files/
+

modules/datasets/doc/datasets/or_sun.rst

+SUN Database
+============
+.. ocv:class:: OR_sun
+
+Implements loading dataset:
+
+_`"SUN Database"`: http://sundatabase.mit.edu/
+
+Currently implemented loading "Scene Recognition Benchmark. SUN397". Planned to implement also "Object Detection Benchmark. SUN2012". 
+
+.. note:: Usage
+
+ 1. From link above download dataset file: SUN397.tar
+
+ 2. Unpack it.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_or_sun -p=/home/user/path_to_unpacked_folder/SUN397/
+

modules/datasets/doc/datasets/pd_caltech.rst

+Caltech Pedestrian Detection Benchmark
+======================================
+.. ocv:class:: PD_caltech
+
+Implements loading dataset:
+
+_`"Caltech Pedestrian Detection Benchmark"`: http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/
+
+.. note:: First version of Caltech Pedestrian dataset loading.
+
+ Code to unpack all frames from seq files commented as their number is huge!
+ So currently load only meta information without data.
+
+ Also ground truth isn't processed, as need to convert it from mat files first.
+
+.. note:: Usage
+
+ 1. From link above download dataset files: set00.tar-set10.tar.
+
+ 2. Unpack them to separate folder.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_pd_caltech -p=/home/user/path_to_unpacked_folders/
+

modules/datasets/doc/datasets/slam_kitti.rst

+KITTI Vision Benchmark
+======================
+.. ocv:class:: SLAM_kitti
+
+Implements loading dataset:
+
+_`"KITTI Vision Benchmark"`: http://www.cvlibs.net/datasets/kitti/eval_odometry.php
+
+.. note:: Usage
+
+ 1. From link above download "Odometry" dataset files: data_odometry_gray\\data_odometry_color\\data_odometry_velodyne\\data_odometry_poses\\data_odometry_calib.zip.
+
+ 2. Unpack data_odometry_poses.zip, it creates folder dataset/poses/. After that unpack data_odometry_gray.zip, data_odometry_color.zip, data_odometry_velodyne.zip. Folder dataset/sequences/ will be created with folders 00/..21/. Each of these folders will contain: image_0/, image_1/, image_2/, image_3/, velodyne/ and files calib.txt & times.txt. These two last files will be replaced after unpacking data_odometry_calib.zip at the end.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_slam_kitti -p=/home/user/path_to_unpacked_folder/dataset/
+

modules/datasets/doc/datasets/slam_tumindoor.rst

+TUMindoor Dataset
+=================
+.. ocv:class:: SLAM_tumindoor
+
+Implements loading dataset:
+
+_`"TUMindoor Dataset"`: http://www.navvis.lmt.ei.tum.de/dataset/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: dslr\\info\\ladybug\\pointcloud.tar.bz2 for each dataset: 11-11-28 (1st floor)\\11-12-13 (1st floor N1)\\11-12-17a (4th floor)\\11-12-17b (3rd floor)\\11-12-17c (Ground I)\\11-12-18a (Ground II)\\11-12-18b (2nd floor)
+
+ 2. Unpack them in separate folder for each dataset. dslr.tar.bz2 -> dslr/, info.tar.bz2 -> info/, ladybug.tar.bz2 -> ladybug/, pointcloud.tar.bz2 -> pointcloud/.
+
+ 3. To load each dataset run: ./opencv/build/bin/example_datasets_slam_tumindoor -p=/home/user/path_to_unpacked_folders/
+

modules/datasets/doc/datasets/tr_chars.rst

+The Chars74K Dataset
+====================
+.. ocv:class:: TR_chars
+
+Implements loading dataset:
+
+_`"The Chars74K Dataset"`: http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/
+
+.. note:: Usage
+
+ 1. From link above download dataset files: EnglishFnt\\EnglishHnd\\EnglishImg\\KannadaHnd\\KannadaImg.tgz, ListsTXT.tgz.
+
+ 2. Unpack them.
+
+ 3. Move .m files from folder ListsTXT/ to appropriate folder. For example, English/list_English_Img.m for EnglishImg.tgz.
+
+ 4. To load data, for example "EnglishImg", run: ./opencv/build/bin/example_datasets_tr_chars -p=/home/user/path_to_unpacked_folder/English/
+

modules/datasets/doc/datasets/tr_svt.rst

+The Street View Text Dataset
+============================
+.. ocv:class:: TR_svt
+
+Implements loading dataset:
+
+_`"The Street View Text Dataset"`: http://vision.ucsd.edu/~kai/svt/
+
+.. note:: Usage
+
+ 1. From link above download dataset file: svt.zip.
+
+ 2. Unpack it.
+
+ 3. To load data run: ./opencv/build/bin/example_datasets_tr_svt -p=/home/user/path_to_unpacked_folder/svt/svt1/
+

modules/datasetstools/include/opencv2/datasetstools/ar_hmdb.hpp → modules/datasets/include/opencv2/datasets/ar_hmdb.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_AR_HMDB_HPP
-#define OPENCV_DATASETSTOOLS_AR_HMDB_HPP
+#ifndef OPENCV_DATASETS_AR_HMDB_HPP
+#define OPENCV_DATASETS_AR_HMDB_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct AR_hmdbObj : public Object

modules/datasetstools/include/opencv2/datasetstools/ar_sports.hpp → modules/datasets/include/opencv2/datasets/ar_sports.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_AR_SPORTS_HPP
-#define OPENCV_DATASETSTOOLS_AR_SPORTS_HPP
+#ifndef OPENCV_DATASETS_AR_SPORTS_HPP
+#define OPENCV_DATASETS_AR_SPORTS_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct AR_sportsObj : public Object

modules/datasetstools/include/opencv2/datasetstools/dataset.hpp → modules/datasets/include/opencv2/datasets/dataset.hpp

@@ -39,8 +39,8 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_DATASET_HPP
-#define OPENCV_DATASETSTOOLS_DATASET_HPP
+#ifndef OPENCV_DATASETS_DATASET_HPP
+#define OPENCV_DATASETS_DATASET_HPP
 
 #include <string>
 #include <vector>
@@ -49,7 +49,7 @@
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct Object

modules/datasetstools/include/opencv2/datasetstools/fr_lfw.hpp → modules/datasets/include/opencv2/datasets/fr_lfw.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_FR_LFW_HPP
-#define OPENCV_DATASETSTOOLS_FR_LFW_HPP
+#ifndef OPENCV_DATASETS_FR_LFW_HPP
+#define OPENCV_DATASETS_FR_LFW_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct FR_lfwObj : public Object

modules/datasetstools/include/opencv2/datasetstools/gr_chalearn.hpp → modules/datasets/include/opencv2/datasets/gr_chalearn.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_GR_CHALEARN_HPP
-#define OPENCV_DATASETSTOOLS_GR_CHALEARN_HPP
+#ifndef OPENCV_DATASETS_GR_CHALEARN_HPP
+#define OPENCV_DATASETS_GR_CHALEARN_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct groundTruth

modules/datasetstools/include/opencv2/datasetstools/gr_skig.hpp → modules/datasets/include/opencv2/datasets/gr_skig.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_GR_SKIG_HPP
-#define OPENCV_DATASETSTOOLS_GR_SKIG_HPP
+#ifndef OPENCV_DATASETS_GR_SKIG_HPP
+#define OPENCV_DATASETS_GR_SKIG_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 enum actionType

modules/datasetstools/include/opencv2/datasetstools/hpe_parse.hpp → modules/datasets/include/opencv2/datasets/hpe_parse.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_HPE_PARSE_HPP
-#define OPENCV_DATASETSTOOLS_HPE_PARSE_HPP
+#ifndef OPENCV_DATASETS_HPE_PARSE_HPP
+#define OPENCV_DATASETS_HPE_PARSE_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct HPE_parseObj : public Object

modules/datasetstools/include/opencv2/datasetstools/ir_affine.hpp → modules/datasets/include/opencv2/datasets/ir_affine.hpp

@@ -39,20 +39,20 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_IR_AFFINE_HPP
-#define OPENCV_DATASETSTOOLS_IR_AFFINE_HPP
+#ifndef OPENCV_DATASETS_IR_AFFINE_HPP
+#define OPENCV_DATASETS_IR_AFFINE_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 #include <opencv2/core/matx.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct IR_affineObj : public Object

modules/datasetstools/include/opencv2/datasetstools/ir_robot.hpp → modules/datasets/include/opencv2/datasets/ir_robot.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_IR_ROBOT_HPP
-#define OPENCV_DATASETSTOOLS_IR_ROBOT_HPP
+#ifndef OPENCV_DATASETS_IR_ROBOT_HPP
+#define OPENCV_DATASETS_IR_ROBOT_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 // calibration matrix from calibrationFile.mat

modules/datasetstools/include/opencv2/datasetstools/is_bsds.hpp → modules/datasets/include/opencv2/datasets/is_bsds.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_IS_BSDS_HPP
-#define OPENCV_DATASETSTOOLS_IS_BSDS_HPP
+#ifndef OPENCV_DATASETS_IS_BSDS_HPP
+#define OPENCV_DATASETS_IS_BSDS_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct IS_bsdsObj : public Object

modules/datasetstools/include/opencv2/datasetstools/is_weizmann.hpp → modules/datasets/include/opencv2/datasets/is_weizmann.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_IS_WEIZMANN_HPP
-#define OPENCV_DATASETSTOOLS_IS_WEIZMANN_HPP
+#ifndef OPENCV_DATASETS_IS_WEIZMANN_HPP
+#define OPENCV_DATASETS_IS_WEIZMANN_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct IS_weizmannObj : public Object

modules/datasetstools/include/opencv2/datasetstools/msm_epfl.hpp → modules/datasets/include/opencv2/datasets/msm_epfl.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_MSM_EPFL_HPP
-#define OPENCV_DATASETSTOOLS_MSM_EPFL_HPP
+#ifndef OPENCV_DATASETS_MSM_EPFL_HPP
+#define OPENCV_DATASETS_MSM_EPFL_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct cameraParam

modules/datasetstools/include/opencv2/datasetstools/msm_middlebury.hpp → modules/datasets/include/opencv2/datasets/msm_middlebury.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_MSM_MIDDLEBURY_HPP
-#define OPENCV_DATASETSTOOLS_MSM_MIDDLEBURY_HPP
+#ifndef OPENCV_DATASETS_MSM_MIDDLEBURY_HPP
+#define OPENCV_DATASETS_MSM_MIDDLEBURY_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct MSM_middleburyObj : public Object

modules/datasetstools/include/opencv2/datasetstools/or_imagenet.hpp → modules/datasets/include/opencv2/datasets/or_imagenet.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_OR_IMAGENET_HPP
-#define OPENCV_DATASETSTOOLS_OR_IMAGENET_HPP
+#ifndef OPENCV_DATASETS_OR_IMAGENET_HPP
+#define OPENCV_DATASETS_OR_IMAGENET_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct OR_imagenetObj : public Object

modules/datasetstools/include/opencv2/datasetstools/or_mnist.hpp → modules/datasets/include/opencv2/datasets/or_mnist.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_OR_MNIST_HPP
-#define OPENCV_DATASETSTOOLS_OR_MNIST_HPP
+#ifndef OPENCV_DATASETS_OR_MNIST_HPP
+#define OPENCV_DATASETS_OR_MNIST_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct OR_mnistObj : public Object

modules/datasetstools/include/opencv2/datasetstools/or_sun.hpp → modules/datasets/include/opencv2/datasets/or_sun.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_OR_SUN_HPP
-#define OPENCV_DATASETSTOOLS_OR_SUN_HPP
+#ifndef OPENCV_DATASETS_OR_SUN_HPP
+#define OPENCV_DATASETS_OR_SUN_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct OR_sunObj : public Object

modules/datasets/include/opencv2/datasets/pd_caltech.hpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2014, Itseez Inc, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Itseez Inc or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_DATASETS_PD_CALTECH_HPP
+#define OPENCV_DATASETS_PD_CALTECH_HPP
+
+#include <string>
+#include <vector>
+
+#include "opencv2/datasets/dataset.hpp"
+
+#include <opencv2/core.hpp>
+
+namespace cv
+{
+namespace datasets
+{
+
+struct PD_caltechObj : public Object
+{
+    //double groundTrue[][];
+    //Mat image;
+    std::string name;
+    std::vector< std::string > imageNames;
+};
+
+//
+// first version of Caltech Pedestrian dataset loading
+// code to unpack all frames from seq files commented as their number is huge
+// so currently load only meta information without data
+//
+// also ground truth isn't processed, as need to convert it from mat files first
+//
+
+class CV_EXPORTS PD_caltech : public Dataset
+{
+public:
+    virtual void load(const std::string &path) = 0;
+
+    static Ptr<PD_caltech> create();
+};
+
+}
+}
+
+#endif

modules/datasetstools/include/opencv2/datasetstools/slam_kitti.hpp → modules/datasets/include/opencv2/datasets/slam_kitti.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_SLAM_KITTI_HPP
-#define OPENCV_DATASETSTOOLS_SLAM_KITTI_HPP
+#ifndef OPENCV_DATASETS_SLAM_KITTI_HPP
+#define OPENCV_DATASETS_SLAM_KITTI_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct pose

modules/datasetstools/include/opencv2/datasetstools/slam_tumindoor.hpp → modules/datasets/include/opencv2/datasets/slam_tumindoor.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_SLAM_TUMINDOOR_HPP
-#define OPENCV_DATASETSTOOLS_SLAM_TUMINDOOR_HPP
+#ifndef OPENCV_DATASETS_SLAM_TUMINDOOR_HPP
+#define OPENCV_DATASETS_SLAM_TUMINDOOR_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 enum imageType

modules/datasetstools/include/opencv2/datasetstools/tr_chars.hpp → modules/datasets/include/opencv2/datasets/tr_chars.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_TR_CHARS_HPP
-#define OPENCV_DATASETSTOOLS_TR_CHARS_HPP
+#ifndef OPENCV_DATASETS_TR_CHARS_HPP
+#define OPENCV_DATASETS_TR_CHARS_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct TR_charsObj : public Object

modules/datasetstools/include/opencv2/datasetstools/tr_svt.hpp → modules/datasets/include/opencv2/datasets/tr_svt.hpp

@@ -39,19 +39,19 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_TR_SVT_HPP
-#define OPENCV_DATASETSTOOLS_TR_SVT_HPP
+#ifndef OPENCV_DATASETS_TR_SVT_HPP
+#define OPENCV_DATASETS_TR_SVT_HPP
 
 #include <string>
 #include <vector>
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
 
 #include <opencv2/core.hpp>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 struct tag

modules/datasetstools/include/opencv2/datasetstools/util.hpp → modules/datasets/include/opencv2/datasets/util.hpp

@@ -39,8 +39,8 @@
 //
 //M*/
 
-#ifndef OPENCV_DATASETSTOOLS_UTIL_HPP
-#define OPENCV_DATASETSTOOLS_UTIL_HPP
+#ifndef OPENCV_DATASETS_UTIL_HPP
+#define OPENCV_DATASETS_UTIL_HPP
 
 #include <string>
 #include <vector>
@@ -49,12 +49,14 @@
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
-void split(const std::string &s, std::vector<std::string> &elems, char delim);
+void CV_EXPORTS split(const std::string &s, std::vector<std::string> &elems, char delim);
 
-void getDirList(const std::string &dirName, std::vector<std::string> &fileNames);
+void CV_EXPORTS createDirectory(const std::string &path);
+
+void CV_EXPORTS getDirList(const std::string &dirName, std::vector<std::string> &fileNames);
 
 }
 }

modules/datasetstools/samples/ar_hmdb.cpp → modules/datasets/samples/ar_hmdb.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ar_hmdb.hpp"
+#include "opencv2/datasets/ar_hmdb.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasets/samples/ar_hmdb_benchmark.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2014, Itseez Inc, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Itseez Inc or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "opencv2/datasets/ar_hmdb.hpp"
+#include "opencv2/datasets/util.hpp"
+
+#include <opencv2/core.hpp>
+#include <opencv2/flann.hpp>
+#include <opencv2/ml.hpp>
+
+#include <cstdio>
+
+#include <string>
+#include <vector>
+#include <fstream>
+
+using namespace std;
+using namespace cv;
+using namespace cv::datasets;
+using namespace cv::flann;
+using namespace cv::ml;
+
+unsigned int getNumFiles(vector< Ptr<Object> > &curr);
+unsigned int getNumFiles(vector< Ptr<Object> > &curr)
+{
+    unsigned int numFiles = 0;
+    for (unsigned int i=0; i<curr.size(); ++i)
+    {
+        AR_hmdbObj *example = static_cast<AR_hmdbObj *>(curr[i].get());
+        vector<string> &videoNames = example->videoNames;
+        for (vector<string>::iterator it=videoNames.begin(); it!=videoNames.end(); ++it)
+        {
+            numFiles++;
+        }
+    }
+
+    return numFiles;
+}
+
+void fillData(const string &path, vector< Ptr<Object> > &curr, Index &flann_index, Mat1f &data, Mat1i &labels);
+void fillData(const string &path, vector< Ptr<Object> > &curr, Index &flann_index, Mat1f &data, Mat1i &labels)
+{
+    const unsigned int descriptorNum = 162;
+    Mat1f sample(1, descriptorNum);
+    Mat1i nresps(1, 1);
+    Mat1f dists(1, 1);
+
+    unsigned int numFiles = 0;
+    for (unsigned int i=0; i<curr.size(); ++i)
+    {
+        AR_hmdbObj *example = static_cast<AR_hmdbObj *>(curr[i].get());
+        vector<string> &videoNames = example->videoNames;
+        for (vector<string>::iterator it=videoNames.begin(); it!=videoNames.end(); ++it)
+        {
+            string featuresFile = *it + ".txt";
+            string featuresFullPath = path + "hmdb51_org_stips/" + example->name + "/" + featuresFile;
+
+            ifstream infile(featuresFullPath.c_str());
+            string line;
+            // skip header
+            for (unsigned int j=0; j<3; ++j)
+            {
+                getline(infile, line);
+            }
+            while (getline(infile, line))
+            {
+                // 7 skip, hog+hof: 72+90 read
+                vector<string> elems;
+                split(line, elems, '\t');
+
+                for (unsigned int j=0; j<descriptorNum; ++j)
+                {
+                    sample(0, j) = (float)atof(elems[j+7].c_str());
+                }
+
+                flann_index.knnSearch(sample, nresps, dists, 1, SearchParams());
+                data(numFiles, nresps(0, 0)) ++;
+            }
+            labels(numFiles, 0) = i;
+            numFiles++;
+        }
+    }
+}
+
+int main(int argc, char *argv[])
+{
+    const char *keys =
+            "{ help h usage ? |    | show this message }"
+            "{ path p         |true| path to dataset }";
+    CommandLineParser parser(argc, argv, keys);
+    string path(parser.get<string>("path"));
+    if (parser.has("help") || path=="true")
+    {
+        parser.printMessage();
+        return -1;
+    }
+
+    // loading dataset
+    Ptr<AR_hmdb> dataset = AR_hmdb::create();
+    dataset->load(path);
+
+    int numSplits = dataset->getNumSplits();
+    printf("splits number: %u\n", numSplits);
+
+
+    const unsigned int descriptorNum = 162;
+    const unsigned int clusterNum = 4000;
+    const unsigned int sampleNum = 5613856; // max for all 3 splits
+
+    vector<double> res;
+    for (int currSplit=0; currSplit<numSplits; ++currSplit)
+    {
+
+        Mat1f samples(sampleNum, descriptorNum);
+        unsigned int currSample = 0;
+        vector< Ptr<Object> > &curr = dataset->getTrain(currSplit);
+        unsigned int numTrainFiles = getNumFiles(curr);
+        unsigned int numFeatures = 0;
+        for (unsigned int i=0; i<curr.size(); ++i)
+        {
+            AR_hmdbObj *example = static_cast<AR_hmdbObj *>(curr[i].get());
+            vector<string> &videoNames = example->videoNames;
+            for (vector<string>::iterator it=videoNames.begin(); it!=videoNames.end(); ++it)
+            {
+                string featuresFile = *it + ".txt";
+                string featuresFullPath = path + "hmdb51_org_stips/" + example->name + "/" + featuresFile;
+
+                ifstream infile(featuresFullPath.c_str());
+                string line;
+                // skip header
+                for (unsigned int j=0; j<3; ++j)
+                {
+                    getline(infile, line);
+                }
+                while (getline(infile, line))
+                {
+                    numFeatures++;
+                    if (currSample < sampleNum)
+                    {
+                        // 7 skip, hog+hof: 72+90 read
+                        vector<string> elems;
+                        split(line, elems, '\t');
+
+                        for (unsigned int j=0; j<descriptorNum; ++j)
+                        {
+                            samples(currSample, j) = (float)atof(elems[j+7].c_str());
+                        }
+                        currSample++;
+                    }
+                }
+            }
+        }
+        printf("split %u, train features number: %u, samples number: %u\n", currSplit, numFeatures, currSample);
+
+        // clustering
+        Mat1f centers(clusterNum, descriptorNum);
+        ::cvflann::KMeansIndexParams kmean_params;
+        unsigned int resultClusters = hierarchicalClustering< L2<float> >(samples, centers, kmean_params);
+        if (resultClusters < clusterNum)
+        {
+            centers = centers.rowRange(Range(0, resultClusters));
+        }
+        Index flann_index(centers, KDTreeIndexParams());
+        printf("resulted clusters number: %u\n", resultClusters);
+
+
+        Mat1f trainData(numTrainFiles, resultClusters);
+        Mat1i trainLabels(numTrainFiles, 1);
+
+        for (unsigned int i=0; i<numTrainFiles; ++i)
+        {
+            for (unsigned int j=0; j<resultClusters; ++j)
+            {
+                trainData(i, j) = 0;
+            }
+        }
+
+        printf("calculating train histograms\n");
+        fillData(path, curr, flann_index, trainData, trainLabels);
+
+        printf("train svm\n");
+        SVM::Params params;
+        params.svmType = SVM::C_SVC;
+        params.kernelType = SVM::POLY; //SVM::RBF;
+        params.degree = 0.5;
+        params.gamma = 1;
+        params.coef0 = 1;
+        params.C = 1;
+        params.nu = 0.5;
+        params.p = 0;
+        params.termCrit = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 1000, 0.01);
+        Ptr<SVM> svm = SVM::create(params);
+        svm->train(trainData, ROW_SAMPLE, trainLabels);
+
+        // prepare to predict
+        curr = dataset->getTest(currSplit);
+        unsigned int numTestFiles = getNumFiles(curr);
+        Mat1f testData(numTestFiles, resultClusters);
+        Mat1i testLabels(numTestFiles, 1); // ground true
+
+        for (unsigned int i=0; i<numTestFiles; ++i)
+        {
+            for (unsigned int j=0; j<resultClusters; ++j)
+            {
+                testData(i, j) = 0;
+            }
+        }
+
+        printf("calculating test histograms\n");
+        fillData(path, curr, flann_index, testData, testLabels);
+
+        printf("predicting\n");
+        Mat1f testPredicted(numTestFiles, 1);
+        svm->predict(testData, testPredicted);
+
+        unsigned int correct = 0;
+        for (unsigned int i=0; i<numTestFiles; ++i)
+        {
+            if ((int)testPredicted(i, 0) == testLabels(i, 0))
+            {
+                correct++;
+            }
+        }
+        double accuracy = 1.0*correct/numTestFiles;
+        printf("correctly recognized actions: %f\n", accuracy);
+        res.push_back(accuracy);
+
+    }
+
+    double accuracy = 0.0;
+    for (unsigned int i=0; i<res.size(); ++i)
+    {
+        accuracy += res[i];
+    }
+    printf("average: %f\n", accuracy/res.size());
+
+    return 0;
+}

modules/datasetstools/samples/ar_sports.cpp → modules/datasets/samples/ar_sports.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ar_sports.hpp"
+#include "opencv2/datasets/ar_sports.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -51,7 +51,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/fr_lfw.cpp → modules/datasets/samples/fr_lfw.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/fr_lfw.hpp"
+#include "opencv2/datasets/fr_lfw.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasets/samples/fr_lfw_benchmark.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2014, Itseez Inc, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Itseez Inc or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+
+#include "opencv2/face.hpp"
+#include "opencv2/datasets/fr_lfw.hpp"
+
+#include <iostream>
+
+#include <cstdio>
+
+#include <string>
+#include <vector>
+#include <map>
+
+using namespace std;
+using namespace cv;
+using namespace cv::datasets;
+using namespace cv::face;
+
+map<string, int> people;
+
+int getLabel(const string &imagePath);
+int getLabel(const string &imagePath)
+{
+    size_t pos = imagePath.find('/');
+    string curr = imagePath.substr(0, pos);
+    map<string, int>::iterator it = people.find(curr);
+    if (people.end() == it)
+    {
+        people.insert(make_pair(curr, (int)people.size()));
+        it = people.find(curr);
+    }
+    return (*it).second;
+}
+
+int main(int argc, const char *argv[])
+{
+    const char *keys =
+            "{ help h usage ? |    | show this message }"
+            "{ path p         |true| path to dataset (lfw2 folder) }";
+    CommandLineParser parser(argc, argv, keys);
+    string path(parser.get<string>("path"));
+    if (parser.has("help") || path=="true")
+    {
+        parser.printMessage();
+        return -1;
+    }
+
+    // These vectors hold the images and corresponding labels.
+    vector<Mat> images;
+    vector<int> labels;
+
+    // load dataset
+    Ptr<FR_lfw> dataset = FR_lfw::create();
+    dataset->load(path);
+
+    unsigned int numSplits = dataset->getNumSplits();
+    printf("splits number: %u\n", numSplits);
+    printf("train size: %u\n", (unsigned int)dataset->getTrain().size());
+    printf("test size: %u\n", (unsigned int)dataset->getTest().size());
+
+    for (unsigned int i=0; i<dataset->getTrain().size(); ++i)
+    {
+        FR_lfwObj *example = static_cast<FR_lfwObj *>(dataset->getTrain()[i].get());
+
+        int currNum = getLabel(example->image1);
+        Mat img = imread(path+example->image1, IMREAD_GRAYSCALE);
+        images.push_back(img);
+        labels.push_back(currNum);
+
+        currNum = getLabel(example->image2);
+        img = imread(path+example->image2, IMREAD_GRAYSCALE);
+        images.push_back(img);
+        labels.push_back(currNum);
+    }
+
+    // 2200 pairsDevTrain, first split: correct: 373, from: 600 -> 62.1667%
+    Ptr<FaceRecognizer> model = createLBPHFaceRecognizer();
+    // 2200 pairsDevTrain, first split: correct: correct: 369, from: 600 -> 61.5%
+    //Ptr<FaceRecognizer> model = createEigenFaceRecognizer();
+    // 2200 pairsDevTrain, first split: correct: 372, from: 600 -> 62%
+    //Ptr<FaceRecognizer> model = createFisherFaceRecognizer();
+
+    model->train(images, labels);
+    //string saveModelPath = "face-rec-model.txt";
+    //cout << "Saving the trained model to " << saveModelPath << endl;
+    //model->save(saveModelPath);
+
+    vector<double> p;
+    for (unsigned int j=0; j<numSplits; ++j)
+    {
+        unsigned int incorrect = 0, correct = 0;
+        vector < Ptr<Object> > &curr = dataset->getTest(j);
+        for (unsigned int i=0; i<curr.size(); ++i)
+        {
+            FR_lfwObj *example = static_cast<FR_lfwObj *>(curr[i].get());
+
+            //int currNum = getLabel(example->image1);
+            Mat img = imread(path+example->image1, IMREAD_GRAYSCALE);
+            int predictedLabel1 = model->predict(img);
+
+            //currNum = getLabel(example->image2);
+            img = imread(path+example->image2, IMREAD_GRAYSCALE);
+            int predictedLabel2 = model->predict(img);
+
+            if ((predictedLabel1 == predictedLabel2 && example->same) ||
+                (predictedLabel1 != predictedLabel2 && !example->same))
+            {
+                correct++;
+            } else
+            {
+                incorrect++;
+            }
+        }
+        p.push_back(1.0*correct/(correct+incorrect));
+        printf("correct: %u, from: %u -> %f\n", correct, correct+incorrect, p.back());
+    }
+    double mu = 0.0;
+    for (vector<double>::iterator it=p.begin(); it!=p.end(); ++it)
+    {
+        mu += *it;
+    }
+    mu /= p.size();
+    double sigma = 0.0;
+    for (vector<double>::iterator it=p.begin(); it!=p.end(); ++it)
+    {
+        sigma += (*it - mu)*(*it - mu);
+    }
+    sigma = sqrt(sigma/p.size());
+    double se = sigma/sqrt(p.size());
+    printf("estimated mean accuracy: %f and the standard error of the mean: %f\n", mu, se);
+
+    return 0;
+}

modules/datasetstools/samples/gr_chalearn.cpp → modules/datasets/samples/gr_chalearn.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/gr_chalearn.hpp"
+#include "opencv2/datasets/gr_chalearn.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/gr_skig.cpp → modules/datasets/samples/gr_skig.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/gr_skig.hpp"
+#include "opencv2/datasets/gr_skig.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -51,7 +51,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/hpe_parse.cpp → modules/datasets/samples/hpe_parse.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/hpe_parse.hpp"
+#include "opencv2/datasets/hpe_parse.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/ir_affine.cpp → modules/datasets/samples/ir_affine.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ir_affine.hpp"
+#include "opencv2/datasets/ir_affine.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -51,7 +51,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/ir_robot.cpp → modules/datasets/samples/ir_robot.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ir_robot.hpp"
+#include "opencv2/datasets/ir_robot.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/is_bsds.cpp → modules/datasets/samples/is_bsds.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/is_bsds.hpp"
+#include "opencv2/datasets/is_bsds.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/is_weizmann.cpp → modules/datasets/samples/is_weizmann.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/is_weizmann.hpp"
+#include "opencv2/datasets/is_weizmann.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/msm_epfl.cpp → modules/datasets/samples/msm_epfl.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/msm_epfl.hpp"
+#include "opencv2/datasets/msm_epfl.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/msm_middlebury.cpp → modules/datasets/samples/msm_middlebury.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/msm_middlebury.hpp"
+#include "opencv2/datasets/msm_middlebury.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/or_imagenet.cpp → modules/datasets/samples/or_imagenet.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_imagenet.hpp"
+#include "opencv2/datasets/or_imagenet.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -52,7 +52,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/or_mnist.cpp → modules/datasets/samples/or_mnist.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_mnist.hpp"
+#include "opencv2/datasets/or_mnist.hpp"
 
 #include <opencv2/core.hpp>
 #include <opencv2/imgcodecs.hpp>
@@ -51,13 +51,13 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {
     const char *keys =
             "{ help h usage ? |    | show this message }"
-            "{ path p         |true| path to dataset (SUN397 folder) }";
+            "{ path p         |true| path to dataset }";
     CommandLineParser parser(argc, argv, keys);
     string path(parser.get<string>("path"));
     if (parser.has("help") || path=="true")

modules/datasetstools/samples/or_sun.cpp → modules/datasets/samples/or_sun.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_sun.hpp"
+#include "opencv2/datasets/or_sun.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasets/samples/pd_caltech.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2014, Itseez Inc, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Itseez Inc or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "opencv2/datasets/pd_caltech.hpp"
+
+#include <opencv2/core.hpp>
+
+#include <cstdio>
+
+#include <string>
+#include <vector>
+
+using namespace std;
+using namespace cv;
+using namespace cv::datasets;
+
+int main(int argc, char *argv[])
+{
+    const char *keys =
+            "{ help h usage ? |    | show this message }"
+            "{ path p         |true| path to dataset }";
+    CommandLineParser parser(argc, argv, keys);
+    string path(parser.get<string>("path"));
+    if (parser.has("help") || path=="true")
+    {
+        parser.printMessage();
+        return -1;
+    }
+
+    Ptr<PD_caltech> dataset = PD_caltech::create();
+    dataset->load(path);
+
+    // ***************
+    // dataset contains for each object its images.
+    // currently on loading extract all images to folder path/../images/
+    // For example, let output train size and first element of first object
+    // and number of it's images.
+    printf("train size: %u\n", (unsigned int)dataset->getTrain().size());
+
+    PD_caltechObj *example = static_cast<PD_caltechObj *>(dataset->getTrain()[0].get());
+    printf("first train object:\n");
+    printf("name: %s\n", example->name.c_str());
+    printf("images number: %u\n", (unsigned int)example->imageNames.size());
+    printf("first image name: %s\n", example->imageNames[0].c_str());
+    printf("images were extracted to path/../images/\n");
+
+    return 0;
+}

modules/datasetstools/samples/slam_kitti.cpp → modules/datasets/samples/slam_kitti.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/slam_kitti.hpp"
+#include "opencv2/datasets/slam_kitti.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/slam_tumindoor.cpp → modules/datasets/samples/slam_tumindoor.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/slam_tumindoor.hpp"
+#include "opencv2/datasets/slam_tumindoor.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -50,7 +50,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/tr_chars.cpp → modules/datasets/samples/tr_chars.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/tr_chars.hpp"
+#include "opencv2/datasets/tr_chars.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -51,7 +51,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/samples/tr_svt.cpp → modules/datasets/samples/tr_svt.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/tr_svt.hpp"
+#include "opencv2/datasets/tr_svt.hpp"
 
 #include <opencv2/core.hpp>
 
@@ -51,7 +51,7 @@
 
 using namespace std;
 using namespace cv;
-using namespace cv::datasetstools;
+using namespace cv::datasets;
 
 int main(int argc, char *argv[])
 {

modules/datasetstools/src/ar_hmdb.cpp → modules/datasets/src/ar_hmdb.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ar_hmdb.hpp"
+#include "opencv2/datasets/ar_hmdb.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/ar_sports.cpp → modules/datasets/src/ar_sports.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ar_sports.hpp"
+#include "opencv2/datasets/ar_sports.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/dataset.cpp → modules/datasets/src/dataset.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/dataset.hpp"
+#include "opencv2/datasets/dataset.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/fr_lfw.cpp → modules/datasets/src/fr_lfw.cpp

@@ -39,14 +39,15 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/fr_lfw.hpp"
+#include "opencv2/datasets/fr_lfw.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 #include <map>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;
@@ -82,12 +83,13 @@ void FR_lfwImp::loadDataset(const string &path)
     getDirList(path, fileNames);
     for (vector<string>::iterator it=fileNames.begin(); it!=fileNames.end(); ++it)
     {
-        if ("pairs.txt" == *it)
+        string &name = *it;
+
+        if (name.length()>3 && name.substr(name.length()-4) == ".txt")
         {
             continue;
         }
 
-        string &name = *it;
         vector<string> images;
 
         string pathFace(path + name + "/");
@@ -142,6 +144,37 @@ void FR_lfwImp::loadDataset(const string &path)
 
         num++;
     }
+
+    // dev train loading to train[0]
+    ifstream infile2((path + "pairsDevTrain.txt").c_str());
+    getline(infile2, line); // should 1100
+    while (getline(infile2, line))
+    {
+        vector<string> elems;
+        split(line, elems, '\t');
+
+        Ptr<FR_lfwObj> curr(new FR_lfwObj);
+        string &person1 = elems[0];
+        unsigned int imageNumber1 = atoi(elems[1].c_str())-1;
+        curr->image1 = person1 + "/" + faces[person1][imageNumber1];
+
+        string person2;
+        unsigned int imageNumber2;
+        if (3 == elems.size())
+        {
+            person2 = elems[0];
+            imageNumber2 = atoi(elems[2].c_str())-1;
+            curr->same = true;
+        } else
+        {
+            person2 = elems[2];
+            imageNumber2 = atoi(elems[3].c_str())-1;
+            curr->same = false;
+        }
+        curr->image2 = person2 + "/" + faces[person2][imageNumber2];
+
+        train[0].push_back(curr);
+    }
 }
 
 Ptr<FR_lfw> FR_lfw::create()

modules/datasetstools/src/gr_chalearn.cpp → modules/datasets/src/gr_chalearn.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/gr_chalearn.hpp"
+#include "opencv2/datasets/gr_chalearn.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/gr_skig.cpp → modules/datasets/src/gr_skig.cpp

@@ -39,14 +39,15 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/gr_skig.hpp"
+#include "opencv2/datasets/gr_skig.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 #include <cstring>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/hpe_parse.cpp → modules/datasets/src/hpe_parse.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/hpe_parse.hpp"
+#include "opencv2/datasets/hpe_parse.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/ir_affine.cpp → modules/datasets/src/ir_affine.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ir_affine.hpp"
+#include "opencv2/datasets/ir_affine.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/ir_robot.cpp → modules/datasets/src/ir_robot.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/ir_robot.hpp"
+#include "opencv2/datasets/ir_robot.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/is_bsds.cpp → modules/datasets/src/is_bsds.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/is_bsds.hpp"
+#include "opencv2/datasets/is_bsds.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/is_weizmann.cpp → modules/datasets/src/is_weizmann.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/is_weizmann.hpp"
+#include "opencv2/datasets/is_weizmann.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/msm_epfl.cpp → modules/datasets/src/msm_epfl.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/msm_epfl.hpp"
+#include "opencv2/datasets/msm_epfl.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/msm_middlebury.cpp → modules/datasets/src/msm_middlebury.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/msm_middlebury.hpp"
+#include "opencv2/datasets/msm_middlebury.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/or_imagenet.cpp → modules/datasets/src/or_imagenet.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_imagenet.hpp"
+#include "opencv2/datasets/or_imagenet.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/or_mnist.cpp → modules/datasets/src/or_mnist.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_mnist.hpp"
+#include "opencv2/datasets/or_mnist.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/or_sun.cpp → modules/datasets/src/or_sun.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/or_sun.hpp"
+#include "opencv2/datasets/or_sun.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasets/src/pd_caltech.cpp

+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2014, Itseez Inc, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Itseez Inc or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "opencv2/datasets/pd_caltech.hpp"
+#include "opencv2/datasets/util.hpp"
+#include "precomp.hpp"
+
+namespace cv
+{
+namespace datasets
+{
+
+using namespace std;
+
+class CV_EXPORTS PD_caltechImp : public PD_caltech
+{
+public:
+    PD_caltechImp() {}
+    //PD_caltechImp(const string &path);
+    virtual ~PD_caltechImp() {}
+
+    virtual void load(const string &path);
+
+private:
+    void loadDataset(const string &path);
+};
+
+/*PD_caltechImp::PD_caltechImp(const string &path)
+{
+    loadDataset(path);
+}*/
+
+void PD_caltechImp::load(const string &path)
+{
+    loadDataset(path);
+}
+
+void PD_caltechImp::loadDataset(const string &path)
+{
+    train.push_back(vector< Ptr<Object> >());
+    test.push_back(vector< Ptr<Object> >());
+    validation.push_back(vector< Ptr<Object> >());
+
+    createDirectory((path + "../images/"));
+
+    vector<string> objectNames;
+    getDirList(path, objectNames);
+    for (vector<string>::iterator it=objectNames.begin(); it!=objectNames.end(); ++it)
+    {
+        Ptr<PD_caltechObj> curr(new PD_caltechObj);
+        curr->name = *it;
+
+        string objectPath(path + "../images/" + curr->name + "/");
+        createDirectory(objectPath);
+
+        string seqImagesPath(path + curr->name + "/");
+        vector<string> seqNames;
+        getDirList(seqImagesPath, seqNames);
+        for (vector<string>::iterator itSeq=seqNames.begin(); itSeq!=seqNames.end(); ++itSeq)
+        {
+            string &seqName = *itSeq;
+
+            createDirectory((objectPath + seqName));
+
+            FILE *f = fopen((seqImagesPath + seqName).c_str(), "rb");
+
+            #define SKIP 28+8+512
+            fseek(f, SKIP, SEEK_CUR);
+
+            unsigned int header[9];
+            size_t res = fread(header, 9, 4, f);
+            double fps;
+            res = fread(&fps, 1, 8, f);
+            fseek(f, 432, SEEK_CUR);
+
+            /*printf("width %u\n", header[0]);
+            printf("height %u\n", header[1]);
+            printf("imageBitDepth %u\n", header[2]);
+            printf("imageBitDepthReal %u\n", header[3]);
+            printf("imageSizeBytes %u\n", header[4]);
+            printf("imageFormat %u\n", header[5]);
+            printf("numFrames %u\n", numFrames);
+            printf("fps %f\n", fps);
+            printf("trueImageSize %u\n", header[8]);*/
+            unsigned int numFrames = header[6];
+
+            string ext;
+            switch (header[5])
+            {
+            case 100:
+            case 200:
+                ext = "raw";
+                break;
+            case 101:
+                ext = "brgb8";
+                break;
+            case 102:
+            case 201:
+                ext = "jpg";
+                break;
+            case 103:
+                ext = "jbrgb";
+                break;
+            case 001:
+            case 002:
+                ext = "png";
+                break;
+            }
+
+            for (unsigned int i=0; i<numFrames; ++i)
+            {
+                unsigned int size;
+                res = fread(&size, 1, 4, f);
+
+                char imgName[20];
+                sprintf(imgName, "/%u.%s", i, ext.c_str());
+                curr->imageNames.push_back(imgName);
+
+                // comment fseek and uncomment next block to unpack all frames
+                fseek(f, size, SEEK_CUR);
+                /*char *img = new char[size];
+                fread(img, size, 1, f);
+                string imgPath(objectPath + seqName + imgName);
+                FILE *fImg = fopen(imgPath.c_str(), "wb");
+                fwrite(img, size, 1, fImg);
+                fclose(fImg);
+                delete[] img;*/
+
+                fseek(f, 12, SEEK_CUR);
+            }
+
+            if (0 != res) // should fix unused variable warning
+            {
+                res = 0;
+            }
+
+            fclose(f);
+        }
+
+        train.back().push_back(curr);
+    }
+}
+
+Ptr<PD_caltech> PD_caltech::create()
+{
+    return Ptr<PD_caltechImp>(new PD_caltechImp);
+}
+
+}
+}

modules/datasetstools/src/precomp.hpp → modules/datasets/src/precomp.hpp

@@ -47,6 +47,4 @@
 
 #include <fstream>
 
-#include "opencv2/datasetstools/util.hpp"
-
 #endif

modules/datasetstools/src/slam_kitti.cpp → modules/datasets/src/slam_kitti.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/slam_kitti.hpp"
+#include "opencv2/datasets/slam_kitti.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/slam_tumindoor.cpp → modules/datasets/src/slam_tumindoor.cpp

@@ -39,14 +39,15 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/slam_tumindoor.hpp"
+#include "opencv2/datasets/slam_tumindoor.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 #include <cstring>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/tinyxml2/tinyxml2.cpp → modules/datasets/src/tinyxml2/tinyxml2.cpp

@@ -21,7 +21,7 @@ must not be misrepresented as being the original software.
 distribution.
 */
 
-#include "opencv2/datasetstools/tinyxml2/tinyxml2.h"
+#include "opencv2/datasets/tinyxml2/tinyxml2.h"
 
 #include <new>		// yes, this one new style header, is in the Android SDK.
 #   ifdef ANDROID_NDK

modules/datasetstools/src/tr_chars.cpp → modules/datasets/src/tr_chars.cpp

@@ -39,12 +39,13 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/tr_chars.hpp"
+#include "opencv2/datasets/tr_chars.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/tr_svt.cpp → modules/datasets/src/tr_svt.cpp

@@ -39,14 +39,15 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/tr_svt.hpp"
+#include "opencv2/datasets/tr_svt.hpp"
+#include "opencv2/datasets/util.hpp"
 #include "precomp.hpp"
 
-#include <opencv2/datasetstools/tinyxml2/tinyxml2.h>
+#include <opencv2/datasets/tinyxml2/tinyxml2.h>
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;

modules/datasetstools/src/util.cpp → modules/datasets/src/util.cpp

@@ -39,7 +39,7 @@
 //
 //M*/
 
-#include "opencv2/datasetstools/util.hpp"
+#include "opencv2/datasets/util.hpp"
 
 #include <cstdlib>
 
@@ -48,6 +48,7 @@
 #ifdef __GNUC__
     #include <unistd.h>
     #include <dirent.h>
+    #include <sys/stat.h>
 #else
     #include <io.h>
     #include <direct.h>
@@ -55,7 +56,7 @@
 
 namespace cv
 {
-namespace datasetstools
+namespace datasets
 {
 
 using namespace std;
@@ -70,6 +71,15 @@ void split(const string &s, vector<string> &elems, char delim)
     }
 }
 
+void createDirectory(const string &path)
+{
+#ifdef __GNUC__
+    mkdir(path.c_str(), S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
+#else
+    mkdir(path.c_str());
+#endif
+}
+
 void getDirList(const string &dirName, vector<string> &fileNames)
 {
 #ifdef __GNUC__

modules/datasetstools/CMakeLists.txt

-set(the_description "datasets tools")
-ocv_define_module(datasetstools opencv_core)
-

modules/datasetstools/doc/datasetstools.rst

-*********************************************************
-datasetstools. Tools for working with different datasets.
-*********************************************************
-
-.. highlight:: cpp
-
-The datasetstools module includes classes for working with different datasets.
-
-Action Recognition
-------------------
-
-AR_hmdb
-=======
-.. ocv:class:: AR_hmdb
-
-Implements loading dataset:
-
-_`"HMDB: A Large Human Motion Database"`: http://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/
-
-.. note:: Usage
-
- 1. From link above download dataset files: hmdb51_org.rar & test_train_splits.rar.
-
- 2. Unpack them.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_ar_hmdb -p=/home/user/path_to_unpacked_folders/
-
-AR_sports
-=========
-.. ocv:class:: AR_sports
-
-Implements loading dataset:
-
-_`"Sports-1M Dataset"`: http://cs.stanford.edu/people/karpathy/deepvideo/
-
-.. note:: Usage
-
- 1. From link above download dataset files (git clone https://code.google.com/p/sports-1m-dataset/).
-
- 2. To load data run: ./opencv/build/bin/example_datasetstools_ar_sports -p=/home/user/path_to_downloaded_folders/
-
-Face Recognition
-----------------
-
-FR_lfw
-======
-.. ocv:class:: FR_lfw
-
-Implements loading dataset:
-
-_`"Labeled Faces in the Wild"`: http://vis-www.cs.umass.edu/lfw/
-
-.. note:: Usage
-
- 1. From link above download any dataset file: lfw.tgz\lfwa.tar.gz\lfw-deepfunneled.tgz\lfw-funneled.tgz and file with 10 test splits: pairs.txt.
-
- 2. Unpack dataset file and place pairs.txt in created folder.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_fr_lfw -p=/home/user/path_to_unpacked_folder/lfw2/
-
-Gesture Recognition
--------------------
-
-GR_chalearn
-===========
-.. ocv:class:: GR_chalearn
-
-Implements loading dataset:
-
-_`"ChaLearn Looking at People"`: http://gesture.chalearn.org/
-
-.. note:: Usage
-
- 1. Follow instruction from site above, download files for dataset "Track 3: Gesture Recognition": Train1.zip-Train5.zip, Validation1.zip-Validation3.zip (Register on site: www.codalab.org and accept the terms and conditions of competition: https://www.codalab.org/competitions/991#learn_the_details There are three mirrors for downloading dataset files. When I downloaded data only mirror: "Universitat Oberta de Catalunya" works).
-
- 2. Unpack train archives Train1.zip-Train5.zip to folder Train/, validation archives Validation1.zip-Validation3.zip to folder Validation/
-
- 3. Unpack all archives in Train/ & Validation/ in the folders with the same names, for example: Sample0001.zip to Sample0001/
-
- 4. To load data run: ./opencv/build/bin/example_datasetstools_gr_chalearn -p=/home/user/path_to_unpacked_folders/
-
-GR_skig
-=======
-.. ocv:class:: GR_skig
-
-Implements loading dataset:
-
-_`"Sheffield Kinect Gesture Dataset"`: http://lshao.staff.shef.ac.uk/data/SheffieldKinectGesture.htm
-
-.. note:: Usage
-
- 1. From link above download dataset files: subject1_dep.7z-subject6_dep.7z, subject1_rgb.7z-subject6_rgb.7z.
-
- 2. Unpack them.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_gr_skig -p=/home/user/path_to_unpacked_folders/
-
-Human Pose Estimation
----------------------
-
-HPE_parse
-=========
-.. ocv:class:: HPE_parse
-
-Implements loading dataset:
-
-_`"PARSE Dataset"`: http://www.ics.uci.edu/~dramanan/papers/parse/
-
-.. note:: Usage
-
- 1. From link above download dataset file: people.zip.
-
- 2. Unpack it.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_hpe_parse -p=/home/user/path_to_unpacked_folder/people_all/
-
-Image Registration
-------------------
-
-IR_affine
-=========
-.. ocv:class:: IR_affine
-
-Implements loading dataset:
-
-_`"Affine Covariant Regions Datasets"`: http://www.robots.ox.ac.uk/~vgg/data/data-aff.html
-
-.. note:: Usage
-
- 1. From link above download dataset files: bark\\bikes\\boat\\graf\\leuven\\trees\\ubc\\wall.tar.gz.
-
- 2. Unpack them.
-
- 3. To load data, for example, for "bark", run: ./opencv/build/bin/example_datasetstools_ir_affine -p=/home/user/path_to_unpacked_folder/bark/
-
-IR_robot
-========
-.. ocv:class:: IR_robot
-
-Implements loading dataset:
-
-_`"Robot Data Set"`: http://roboimagedata.compute.dtu.dk/?page_id=24
-
-.. note:: Usage
-
- 1. From link above download files for dataset "Point Feature Data Set – 2010": SET001_6.tar.gz-SET055_60.tar.gz (there are two data sets: - Full resolution images (1200×1600), ~500 Gb and - Half size image (600×800), ~115 Gb.)
- 2. Unpack them to one folder.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_ir_robot -p=/home/user/path_to_unpacked_folder/
-
-Image Segmentation
-------------------
-
-IS_bsds
-=======
-.. ocv:class:: IS_bsds
-
-Implements loading dataset:
-
-_`"The Berkeley Segmentation Dataset and Benchmark"`: https://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/
-
-.. note:: Usage
-
- 1. From link above download dataset files: BSDS300-human.tgz & BSDS300-images.tgz.
-
- 2. Unpack them.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_is_bsds -p=/home/user/path_to_unpacked_folder/BSDS300/
-
-IS_weizmann
-===========
-.. ocv:class:: IS_weizmann
-
-Implements loading dataset:
-
-_`"Weizmann Segmentation Evaluation Database"`: http://www.wisdom.weizmann.ac.il/~vision/Seg_Evaluation_DB/
-
-.. note:: Usage
-
- 1. From link above download dataset files: Weizmann_Seg_DB_1obj.ZIP & Weizmann_Seg_DB_2obj.ZIP.
-
- 2. Unpack them.
-
- 3. To load data, for example, for 1 object dataset, run: ./opencv/build/bin/example_datasetstools_is_weizmann -p=/home/user/path_to_unpacked_folder/1obj/
-
-Multiview Stereo Matching
--------------------------
-
-MSM_epfl
-========
-.. ocv:class:: MSM_epfl
-
-Implements loading dataset:
-
-_`"EPFL Multi-View Stereo"`: http://cvlabwww.epfl.ch/~strecha/multiview/denseMVS.html
-
-.. note:: Usage
-
- 1. From link above download dataset files: castle_dense\\castle_dense_large\\castle_entry\\fountain\\herzjesu_dense\\herzjesu_dense_large_bounding\\cameras\\images\\p.tar.gz.
-
- 2. Unpack them in separate folder for each object. For example, for "fountain", in folder fountain/ : fountain_dense_bounding.tar.gz -> bounding/, fountain_dense_cameras.tar.gz -> camera/, fountain_dense_images.tar.gz -> png/, fountain_dense_p.tar.gz -> P/
-
- 3. To load data, for example, for "fountain", run: ./opencv/build/bin/example_datasetstools_msm_epfl -p=/home/user/path_to_unpacked_folder/fountain/
-
-MSM_middlebury
-==============
-.. ocv:class:: MSM_middlebury
-
-Implements loading dataset:
-
-_`"Stereo – Middlebury Computer Vision"`: http://vision.middlebury.edu/mview/
-
-.. note:: Usage
-
- 1. From link above download dataset files: dino\\dinoRing\\dinoSparseRing\\temple\\templeRing\\templeSparseRing.zip
-
- 2. Unpack them.
-
- 3. To load data, for example "temple" dataset, run: ./opencv/build/bin/example_datasetstools_msm_middlebury -p=/home/user/path_to_unpacked_folder/temple/
-
-Object Recognition
-------------------
-
-OR_imagenet
-===========
-.. ocv:class:: OR_imagenet
-
-Implements loading dataset:
-
-_`"ImageNet"`: http://www.image-net.org/
-
-Currently implemented loading full list with urls. Planned to implement dataset from ILSVRC challenge. 
-
-.. note:: Usage
-
- 1. From link above download dataset file: imagenet_fall11_urls.tgz
-
- 2. Unpack it.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_or_imagenet -p=/home/user/path_to_unpacked_file/
-
-OR_mnist
-===========
-.. ocv:class:: OR_mnist
-
-Implements loading dataset:
-
-_`"MNIST"`: http://yann.lecun.com/exdb/mnist/
-
-.. note:: Usage
-
- 1. From link above download dataset files: t10k-images-idx3-ubyte.gz, t10k-labels-idx1-ubyte.gz, train-images-idx3-ubyte.gz, train-labels-idx1-ubyte.gz.
-
- 2. Unpack them.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_or_mnist -p=/home/user/path_to_unpacked_files/
-
-OR_sun
-======
-.. ocv:class:: OR_sun
-
-Implements loading dataset:
-
-_`"SUN Database"`: http://sundatabase.mit.edu/
-
-Currently implemented loading "Scene Recognition Benchmark. SUN397". Planned to implement also "Object Detection Benchmark. SUN2012". 
-
-.. note:: Usage
-
- 1. From link above download dataset file: SUN397.tar
-
- 2. Unpack it.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_or_sun -p=/home/user/path_to_unpacked_folder/SUN397/
-
-SLAM
-----
-
-SLAM_kitti
-==========
-.. ocv:class:: SLAM_kitti
-
-Implements loading dataset:
-
-_`"KITTI Vision Benchmark"`: http://www.cvlibs.net/datasets/kitti/eval_odometry.php
-
-.. note:: Usage
-
- 1. From link above download "Odometry" dataset files: data_odometry_gray\\data_odometry_color\\data_odometry_velodyne\\data_odometry_poses\\data_odometry_calib.zip.
-
- 2. Unpack data_odometry_poses.zip, it creates folder dataset/poses/. After that unpack data_odometry_gray.zip, data_odometry_color.zip, data_odometry_velodyne.zip. Folder dataset/sequences/ will be created with folders 00/..21/. Each of these folders will contain: image_0/, image_1/, image_2/, image_3/, velodyne/ and files calib.txt & times.txt. These two last files will be replaced after unpacking data_odometry_calib.zip at the end.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_slam_kitti -p=/home/user/path_to_unpacked_folder/dataset/
-
-SLAM_tumindoor
-==============
-.. ocv:class:: SLAM_tumindoor
-
-Implements loading dataset:
-
-_`"TUMindoor Dataset"`: http://www.navvis.lmt.ei.tum.de/dataset/
-
-.. note:: Usage
-
- 1. From link above download dataset files: dslr\\info\\ladybug\\pointcloud.tar.bz2 for each dataset: 11-11-28 (1st floor)\\11-12-13 (1st floor N1)\\11-12-17a (4th floor)\\11-12-17b (3rd floor)\\11-12-17c (Ground I)\\11-12-18a (Ground II)\\11-12-18b (2nd floor)
-
- 2. Unpack them in separate folder for each dataset. dslr.tar.bz2 -> dslr/, info.tar.bz2 -> info/, ladybug.tar.bz2 -> ladybug/, pointcloud.tar.bz2 -> pointcloud/.
-
- 3. To load each dataset run: ./opencv/build/bin/example_datasetstools_slam_tumindoor -p=/home/user/path_to_unpacked_folders/
-
-Text Recognition
-----------------
-
-TR_chars
-========
-.. ocv:class:: TR_chars
-
-Implements loading dataset:
-
-_`"The Chars74K Dataset"`: http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/
-
-.. note:: Usage
-
- 1. From link above download dataset files: EnglishFnt\\EnglishHnd\\EnglishImg\\KannadaHnd\\KannadaImg.tgz, ListsTXT.tgz.
-
- 2. Unpack them.
-
- 3. Move .m files from folder ListsTXT/ to appropriate folder. For example, English/list_English_Img.m for EnglishImg.tgz.
-
- 4. To load data, for example "EnglishImg", run: ./opencv/build/bin/example_datasetstools_tr_chars -p=/home/user/path_to_unpacked_folder/English/
-
-TR_svt
-======
-.. ocv:class:: TR_svt
-
-Implements loading dataset:
-
-_`"The Street View Text Dataset"`: http://vision.ucsd.edu/~kai/svt/
-
-.. note:: Usage
-
- 1. From link above download dataset file: svt.zip.
-
- 2. Unpack it.
-
- 3. To load data run: ./opencv/build/bin/example_datasetstools_tr_svt -p=/home/user/path_to_unpacked_folder/svt/svt1/
-