Maksim Shabunin
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94e777ba45
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Trying to fix some tests
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2015-09-08 16:16:37 +03:00 |
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Vadim Pisarevsky
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4f860dcffa
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Merge pull request #348 from mshabunin:contrib-tests
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2015-08-27 13:37:51 +00:00 |
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Vadim Pisarevsky
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e72e2a10b4
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Merge pull request #352 from kurnianggoro:gsoc_final
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2015-08-27 13:36:47 +00:00 |
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Vadim Pisarevsky
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abe59c33b6
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Merge pull request #340 from RobertaRavanelli:FinalTermPullRequest
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2015-08-27 11:50:22 +00:00 |
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Vadim Pisarevsky
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9cb10bd67e
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Merge pull request #346 from sergarrido:charuco_pr
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2015-08-27 11:49:00 +00:00 |
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Vadim Pisarevsky
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7b1068d8a0
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Merge pull request #351 from sunglok:bugfix_trackerMIL
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2015-08-27 11:37:15 +00:00 |
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Vadim Pisarevsky
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52a113793f
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Merge pull request #349 from SvetlanaFilicheva:ukf-aukf
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2015-08-27 11:33:38 +00:00 |
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Kurnianggoro
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cb35f120a6
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optimization
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2015-08-27 19:00:12 +09:00 |
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Vadim Pisarevsky
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e2f9c66671
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Merge pull request #350 from lluisgomez:ocrbeamsearch_refactor
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2015-08-27 07:50:44 +00:00 |
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Vadim Pisarevsky
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3431d8ae1d
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Merge pull request #286 from Jiaolong:dpm_cascade
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2015-08-27 07:14:53 +00:00 |
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Sunglok Choi
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4a64d57031
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Fixed a minor bug on reading/writing trackerMIL::Param.
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2015-08-27 10:41:52 +09:00 |
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S. Garrido
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7c08b2f7db
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Added aruco module
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2015-08-26 22:18:23 +02:00 |
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Lluis Gomez-Bigorda
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c3042c3f51
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remove trailing space
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2015-08-26 21:47:36 +02:00 |
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Lluis Gomez-Bigorda
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a94753c0bf
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fix Win x64 warning
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2015-08-26 21:17:52 +02:00 |
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Lluis Gomez-Bigorda
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b19c676559
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fix Win x64 and iOS warnings
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2015-08-26 21:04:27 +02:00 |
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Lluis Gomez-Bigorda
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7cd6dbb0c9
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Adds two more examples of croped word recognition, and show how to set the beam size parameter for small lexicon.
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2015-08-26 20:13:15 +02:00 |
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Lluis Gomez-Bigorda
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cc43177675
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OCRBeamSearchDecoder code refactor: fixes most of the TODOs comments, cleans-up code, and fix a bug in score_segmentation(...) member function.
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2015-08-26 20:11:17 +02:00 |
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SvetlanaFilicheva
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450388468d
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Implement Unscented Kalman Filter (UKF) and Augmented UKF
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2015-08-26 18:20:20 +03:00 |
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Vadim Pisarevsky
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ffa6637b94
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Merge pull request #300 from kurnianggoro:multitracker
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2015-08-26 14:12:30 +00:00 |
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jiaolong_x220
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c085810035
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added dpm module
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2015-08-26 08:38:34 +02:00 |
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RobertaRavanelli
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fc98b871b9
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Moved a cout message to avoid an error about the comunication of number of images to project
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2015-08-25 14:58:30 +02:00 |
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RobertaRavanelli
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a03f3815c2
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Added structured_light module
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2015-08-25 14:58:30 +02:00 |
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Vadim Pisarevsky
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60f5e5ef80
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Merge pull request #327 from lluisgomez:svt_dataset
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2015-08-24 17:00:43 +00:00 |
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Vadim Pisarevsky
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f9dab6164c
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Merge pull request #328 from lluisgomez:icdar_dataset
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2015-08-24 17:00:20 +00:00 |
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Vadim Pisarevsky
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254d5b9f71
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Merge pull request #344 from lluisgomez:ocr_character_recognizer
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2015-08-24 13:33:55 +00:00 |
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Lluis Gomez-Bigorda
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45f4bd9828
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Add benchmark code for the Chars74k dataset. Using the CNN character classifier reaches 75% and 84% accuracy for case-sensitive and case-insensitive recognition respectively.
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2015-08-21 18:54:52 +02:00 |
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Lluis Gomez-Bigorda
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0be529da05
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Adds demo program of Scene Text Character Recognition using the CNN classifier.
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2015-08-21 18:20:41 +02:00 |
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Kurnianggoro
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a805f8baf9
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add multitracker and roiselector to tracking API group
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2015-08-21 16:32:48 +09:00 |
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Vadim Pisarevsky
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e18103e2e3
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Merge pull request #221 from xolodilnik:fast_hough_transform
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2015-08-21 06:52:06 +00:00 |
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Maksim Shabunin
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47d45c55de
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ximgproc perftest
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2015-08-20 15:49:29 +03:00 |
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Maksim Shabunin
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fb8d27c987
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perf_line_descriptor
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2015-08-20 15:12:08 +03:00 |
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Maksim Shabunin
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22e57f59e6
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xfeatures2d tests
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2015-08-20 15:03:55 +03:00 |
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Maksim Shabunin
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ba49cfabff
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Testing line_descriptor, reg, rgbd
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2015-08-20 12:19:13 +03:00 |
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Maksim Shabunin
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95af1b58f9
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Tests for xphoto
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2015-08-19 18:03:56 +03:00 |
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Maksim Shabunin
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79df3dbc85
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Tests for ximgproc
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2015-08-19 12:08:42 +03:00 |
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kurnianggoro
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9477193a0e
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Merge pull request #2 from kurnianggoro/roiselector
Wrap the ROISelector class
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2015-08-10 10:01:52 +09:00 |
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Kurnianggoro
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95a32d7618
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new line at EOF
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2015-08-10 09:59:29 +09:00 |
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lluis
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271a9b4091
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Fix w64 warnings
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2015-08-09 08:51:08 +02:00 |
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lluis
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6f4a09ca7e
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Add benchmark for ICDAR2015 dataset using OCRTesseract and ERFilter classes. Gives word spotting f-score 0.642082 with strongly contextualized lexicon (100 words).
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2015-08-09 00:13:40 +02:00 |
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lluis
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be927d962a
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Report the total f1 score (0.37) and not the mean-f1. This is in accordance with the standard SVT evaluation protocol and allows for comparison with other published results.
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2015-08-06 11:59:53 +02:00 |
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lluis
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769d2ada0e
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Changes SVT recognition evaluation to be Case Insensitive (according to the standard evaluation protocol). This makes the benchmark obtained mean-f1 score increase from 0.23 to 0.27
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2015-08-06 11:53:46 +02:00 |
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Lluis Gomez-Bigorda
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306aed4078
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Adds interface for the ICDAR2015 dataset (end-to-end text recognition task)
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2015-08-06 10:54:58 +02:00 |
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Maksim Shabunin
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172fdb3152
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Merge pull request #303 from sbokov:improvingStereoSGBM
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2015-08-06 08:09:33 +00:00 |
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Vadim Pisarevsky
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6e4d6bca75
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Merge pull request #321 from lluisgomez:ocr_refactor_even
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2015-08-05 17:06:07 +00:00 |
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Lluis Gomez-Bigorda
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796c26f68a
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Fix w64 warnings
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2015-08-03 22:15:31 +02:00 |
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Lluis Gomez-Bigorda
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1481194b54
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Fix w64 warnings
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2015-08-03 21:45:45 +02:00 |
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Lluis Gomez-Bigorda
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2315f9ca22
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Minor bugfix: removes unwanted space character at the begining of recognition output strings.
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2015-08-03 20:53:49 +02:00 |
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Lluis Gomez-Bigorda
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2538bf74a6
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Adds example on segmented word recognition. Shows the use of the OCRHMMDecoder with the NM and CNN default classifiers.
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2015-08-03 20:50:33 +02:00 |
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lluis
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ee677a255b
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Overload the run() method in BaseOCR class in order to adapt to different classifier callbacks. The original run() method accepts only one Mat input image, this is expected to be a binarzed image with black and white text and works both with the OCRTesseract class and the OCRHMMDecoder class when the character classifier callback works with binary images (e.g. NM). The new run() method accepts two Mat input parameters. One for the gray scale (or color) source image and the other for a binary mask where each connected component corresponds to a pre-segmented character in the input image. This way the OCRHMMDecoder is able to work with character classifiers that operate in grey scale (or color) images (e.g. a CNN).
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2015-08-01 13:52:24 +02:00 |
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lluis
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c146d37b93
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Better CNN model for character recognition. Trained with an augmented dataset by adding translation/scale variations. Updated the croped word recognition with new class numbering (compatible with previous NM classifier).
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2015-08-01 13:52:00 +02:00 |
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