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Tools for working with different datasets. — OpenCV datasetstools 3.0 documentation - - - - - - - - - - - -
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datasetstools. Tools for working with different datasets.

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The datasetstools module includes classes for working with different datasets.

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First version of this module was implemented for Fall2014 OpenCV Challenge.

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Action Recognition

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ar_hmdb

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Implements loading dataset:

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“HMDB: A Large Human Motion Database”: http://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/

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Note

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Usage

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  1. From link above download dataset files: hmdb51_org.rar & test_train_splits.rar.
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  2. Unpack them.
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  3. To load data run: ./opencv/build/bin/example_datasetstools_ar_hmdb -p=/home/user/path_to_unpacked_folders/
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ar_sports

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Implements loading dataset:

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“Sports-1M Dataset”: http://cs.stanford.edu/people/karpathy/deepvideo/

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Usage

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  1. From link above download dataset files (git clone https://code.google.com/p/sports-1m-dataset/).
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  2. To load data run: ./opencv/build/bin/example_datasetstools_ar_sports -p=/home/user/path_to_downloaded_folders/
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Face Recognition

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fr_lfw

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Implements loading dataset:

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“Labeled Faces in the Wild-a”: http://www.openu.ac.il/home/hassner/data/lfwa/

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Usage

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  1. From link above download dataset file: lfwa.tar.gz.
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  2. Unpack it.
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  3. To load data run: ./opencv/build/bin/example_datasetstools_fr_lfw -p=/home/user/path_to_unpacked_folder/lfw2/
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Gesture Recognition

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gr_chalearn

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Implements loading dataset:

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“ChaLearn Looking at People”: http://gesture.chalearn.org/

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Usage

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  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).
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  2. Unpack train archives Train1.zip-Train5.zip to one folder (currently loading validation files wasn’t implemented)
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  3. To load data run: ./opencv/build/bin/example_datasetstools_gr_chalearn -p=/home/user/path_to_unpacked_folder/
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gr_skig

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Implements loading dataset:

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“Sheffield Kinect Gesture Dataset”: http://lshao.staff.shef.ac.uk/data/SheffieldKinectGesture.htm

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Usage

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  1. From link above download dataset files: subject1_dep.7z-subject6_dep.7z, subject1_rgb.7z-subject6_rgb.7z.
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  2. Unpack them.
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Human Pose Estimation

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hpe_parse

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Implements loading dataset:

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“PARSE Dataset”: http://www.ics.uci.edu/~dramanan/papers/parse/

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Usage

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  1. From link above download dataset file: people.zip.
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  2. Unpack it.
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  3. To load data run: ./opencv/build/bin/example_datasetstools_hpe_parse -p=/home/user/path_to_unpacked_folder/people_all/
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Image Registration

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ir_affine

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Implements loading dataset:

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“Affine Covariant Regions Datasets”: http://www.robots.ox.ac.uk/~vgg/data/data-aff.html

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Usage

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  1. From link above download dataset files: bark\bikes\boat\graf\leuven\trees\ubc\wall.tar.gz.
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  2. Unpack them.
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ir_robot

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Implements loading dataset:

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“Robot Data Set”: http://roboimagedata.compute.dtu.dk/?page_id=24

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Usage

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  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.)
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  2. Unpack them to one folder.
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Image Segmentation

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is_bsds

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Implements loading dataset:

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“The Berkeley Segmentation Dataset and Benchmark”: https://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/

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Usage

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  1. From link above download dataset files: BSDS300-human.tgz & BSDS300-images.tgz.
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  2. Unpack them.
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  3. To load data run: ./opencv/build/bin/example_datasetstools_is_bsds -p=/home/user/path_to_unpacked_folder/BSDS300/
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is_weizmann

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Implements loading dataset:

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“Weizmann Segmentation Evaluation Database”: http://www.wisdom.weizmann.ac.il/~vision/Seg_Evaluation_DB/

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Usage

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  1. From link above download dataset files: Weizmann_Seg_DB_1obj.ZIP & Weizmann_Seg_DB_2obj.ZIP.
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Multiview Stereo Matching

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msm_epfl

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Implements loading dataset:

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“EPFL Multi-View Stereo”: http://cvlabwww.epfl.ch/~strecha/multiview/denseMVS.html

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Usage

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  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.
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  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/
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msm_middlebury

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Implements loading dataset:

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“Stereo – Middlebury Computer Vision”: http://vision.middlebury.edu/mview/

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Usage

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  1. From link above download dataset files: dino\dinoRing\dinoSparseRing\temple\templeRing\templeSparseRing.zip
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Object Recognition

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or_imagenet

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Implements loading dataset:

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“ImageNet”: http://www.image-net.org/

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Currently implemented loading full list with urls. Planned to implement dataset from ILSVRC challenge.

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Usage

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  1. From link above download dataset file: imagenet_fall11_urls.tgz
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or_sun

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Implements loading dataset:

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“SUN Database”: http://sun.cs.princeton.edu/

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Currently implemented loading “Scene Recognition Benchmark. SUN397”. Planned to implement also “Object Detection Benchmark. SUN2012”.

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Usage

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  1. From link above download dataset file: SUN397.tar
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SLAM

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slam_kitti

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Implements loading dataset:

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“KITTI Vision Benchmark”: http://www.cvlibs.net/datasets/kitti/eval_odometry.php

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Usage

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  1. From link above download “Odometry” dataset files: data_odometry_gray\data_odometry_color\data_odometry_velodyne\data_odometry_poses\data_odometry_calib.zip.
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  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.
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slam_tumindoor

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Implements loading dataset:

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“TUMindoor Dataset”: http://www.navvis.lmt.ei.tum.de/dataset/

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Usage

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  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)
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  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/.
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Text Recognition

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tr_chars

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Implements loading dataset:

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“The Chars74K Dataset”: http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/

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Note

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Usage

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  1. From link above download dataset files: EnglishFnt\EnglishHnd\EnglishImg\KannadaHnd\KannadaImg.tgz, ListsTXT.tgz.
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  3. Move *.m files from folder ListsTXT/ to appropriate folder. For example, English/list_English_Img.m for EnglishImg.tgz.
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  4. To load data, for example “EnglishImg”, run: ./opencv/build/bin/example_datasetstools_tr_chars -p=/home/user/path_to_unpacked_folder/English/
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tr_svt

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Implements loading dataset:

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“The Street View Text Dataset”: http://vision.ucsd.edu/~kai/svt/

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Note

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Usage

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  1. From link above download dataset file: svt.zip.
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  3. To load data run: ./opencv/build/bin/example_datasetstools_tr_svt -p=/home/user/path_to_unpacked_folder/svt/svt1/
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Table Of Contents

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