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AlexeyAB f19d1440cb Moved all OpenCV functions to the image_opencv.cpp/h 2019-04-04 22:57:05 +03:00
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log_parser * make regex compatible with new code 2018-08-05 12:18:27 +08:00
windows Fixed mAP calculation for CRNN layer during training 2019-03-05 02:15:44 +03:00
README.md Moved all OpenCV functions to the image_opencv.cpp/h 2019-04-04 22:57:05 +03:00
dice_label.sh Added dice code 2015-08-13 16:02:22 -07:00
gen_anchors.py Update to prevent the error at Line 74: data being one-dimensional 2018-08-15 10:04:14 -07:00
gen_tactic.sh damnit alex 2016-06-06 13:37:30 -07:00
get_coco_dataset.sh get_coco_dataset.sh downloads MS COCO dataset from images.cocodataset.org 2018-12-21 23:07:37 +03:00
get_imagenet_train.sh scripts/README.md 2019-03-03 15:09:41 +03:00
get_openimages_dataset.py Create get_openimages_dataset.py 2018-05-17 15:22:49 +02:00
imagenet_label.sh scripts and stuff 2015-07-20 15:11:01 -07:00
kmeansiou.c Added kmeansiou.c 2017-10-06 00:26:45 +03:00
reval_voc.py Fixed yolo_console_dll.cpp 2017-09-13 13:47:19 +03:00
reval_voc_py3.py Added compute_mAP.cmd for calculation mAP for Pascal VOC 2007 dataset. 2018-02-14 00:25:11 +03:00
voc_eval.py Fixed yolo_console_dll.cpp 2017-09-13 13:47:19 +03:00
voc_eval_py3.py Added compute_mAP.cmd for calculation mAP for Pascal VOC 2007 dataset. 2018-02-14 00:25:11 +03:00
voc_label.py PascalVOC label scripts are updated 2018-07-18 15:08:34 +03:00
voc_label_difficult.py PascalVOC label scripts are updated 2018-07-18 15:08:34 +03:00

README.md

Datasets:

Pascal VOC: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html

MS COCO: http://cocodataset.org/#download

ImageNet: http://imagenet.stanford.edu/download.php

ImageNet (ILSVRC2012): http://www.image-net.org/challenges/LSVRC/2012/nonpub-downloads

ImageNet (ILSVRC2015): http://image-net.org/small/download.php

Open Images: https://storage.googleapis.com/openimages/web/download.html

Cityscapes: https://www.cityscapes-dataset.com/

Object Tracking Benchmark: http://cvlab.hanyang.ac.kr/tracker_benchmark/datasets.html

MOT (Multiple object tracking benchmark): https://motchallenge.net/

VOT (Visual object tracking): http://www.votchallenge.net/challenges.html

FREE FLIR Thermal Dataset (infrared): https://www.flir.eu/oem/adas/adas-dataset-form/

MARS: http://www.liangzheng.com.cn/Project/project_mars.html

Market-1501: http://www.liangzheng.org/Project/project_reid.html

German Traffic Sign Recognition Benchmark: http://benchmark.ini.rub.de/

Labeled Faces in the Wild: http://vis-www.cs.umass.edu/lfw/

Core50: https://vlomonaco.github.io/core50/

Visual Question Answering: https://visualqa.org/download.html

Large Movie Review Dataset: http://ai.stanford.edu/~amaas/data/sentiment/

KITTI (for autonomous driving): http://www.cvlibs.net/datasets/kitti/

nuScenes (for autonomous driving): https://www.nuscenes.org/overview

Wikipedia's List of datasets: https://en.wikipedia.org/wiki/List_of_datasets_for_machine-learning_research

Other datasets (Music, Natural Images, Artificial Datasets, Faces, Text, Speech, Recommendation Systems, Misc): http://deeplearning.net/datasets/

25 datasets: https://www.analyticsvidhya.com/blog/2018/03/comprehensive-collection-deep-learning-datasets/

List of datasets: https://riemenschneider.hayko.at/vision/dataset/index.php

Another list of datasets: http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm

Pedestrian DATASETs for Vision based Detection and Tracking: https://hemprasad.wordpress.com/2014/11/08/pedestrian-datasets-for-vision-based-detection-and-tracking/

TrackingNet: https://tracking-net.org/