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modules/datasets/doc/datasets.rst
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*********************************************************
datasets. Framework for working with different datasets.
*********************************************************
*******************************************************
datasets. Framework for working with different datasets
*******************************************************
.. highlight:: cpp
The datasets module includes classes for working with different datasets.
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
------------------
AR_hmdb
=======
.. ocv:class:: AR_hmdb
:doc:`datasets/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/
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_datasets_ar_sports -p=/home/user/path_to_downloaded_folders/
:doc:`datasets/ar_sports`
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 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/
.. note:: 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: ./opencv/build/bin/example_datasets_fr_lfw_benchmark -p=/home/user/path_to_unpacked_folder/lfw2/
:doc:`datasets/fr_lfw`
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_datasets_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.
:doc:`datasets/gr_chalearn`
3. To load data run: ./opencv/build/bin/example_datasets_gr_skig -p=/home/user/path_to_unpacked_folders/
:doc:`datasets/gr_skig`
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_datasets_hpe_parse -p=/home/user/path_to_unpacked_folder/people_all/
:doc:`datasets/hpe_parse`
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_datasets_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
:doc:`datasets/ir_affine`
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/
:doc:`datasets/ir_robot`
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_datasets_is_bsds -p=/home/user/path_to_unpacked_folder/BSDS300/
IS_weizmann
===========
.. ocv:class:: IS_weizmann
:doc:`datasets/is_bsds`
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/
:doc:`datasets/is_weizmann`
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
:doc:`datasets/msm_epfl`
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/
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_datasets_msm_middlebury -p=/home/user/path_to_unpacked_folder/temple/
:doc:`datasets/msm_middlebury`
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_datasets_or_imagenet -p=/home/user/path_to_unpacked_file/
:doc:`datasets/or_imagenet`
OR_mnist
===========
.. ocv:class:: OR_mnist
:doc:`datasets/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/
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_datasets_or_sun -p=/home/user/path_to_unpacked_folder/SUN397/
:doc:`datasets/or_sun`
Pedestrian Detection
--------------------
PD_caltech
==========
.. 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/
:doc:`datasets/pd_caltech`
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_datasets_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
:doc:`datasets/slam_kitti`
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/
:doc:`datasets/slam_tumindoor`
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_datasets_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.
:doc:`datasets/tr_chars`
3. To load data run: ./opencv/build/bin/example_datasets_tr_svt -p=/home/user/path_to_unpacked_folder/svt/svt1/
:doc:`datasets/tr_svt`
modules/datasets/doc/datasets/ar_hmdb.rst 0 → 100644
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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/
modules/datasets/doc/datasets/ar_sports.rst 0 → 100644
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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 0 → 100644
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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/
.. note:: 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: ./opencv/build/bin/example_datasets_fr_lfw_benchmark -p=/home/user/path_to_unpacked_folder/lfw2/
modules/datasets/doc/datasets/gr_chalearn.rst 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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 0 → 100644
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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/datasets/src/pd_caltech.cpp
View file @ 1d6a0e47
......@@ -167,6 +167,11 @@ void PD_caltechImp::loadDataset(const string &path)
fseek(f, 12, SEEK_CUR);
}
if (0 != res) // should fix unused variable warning
{
res = 0;
}
fclose(f);
}
......
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