Changes
On December 16, 2024 at 6:40:53 PM UTC, admin:
-
Changed value of field
doi_status
toTrue
in ICDAR 2017 MLT -
Changed value of field
doi_date_published
to2024-12-16
in ICDAR 2017 MLT -
Added resource Original Metadata to ICDAR 2017 MLT
f | 1 | { | f | 1 | { |
2 | "access_rights": "", | 2 | "access_rights": "", | ||
3 | "author": "Xuebo Liu", | 3 | "author": "Xuebo Liu", | ||
4 | "author_email": "", | 4 | "author_email": "", | ||
5 | "citation": [], | 5 | "citation": [], | ||
6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
7 | "defined_in": "https://doi.org/10.48550/arXiv.1801.01671", | 7 | "defined_in": "https://doi.org/10.48550/arXiv.1801.01671", | ||
8 | "doi": "10.57702/ody1o6hl", | 8 | "doi": "10.57702/ody1o6hl", | ||
n | 9 | "doi_date_published": null, | n | 9 | "doi_date_published": "2024-12-16", |
10 | "doi_publisher": "TIB", | 10 | "doi_publisher": "TIB", | ||
n | 11 | "doi_status": false, | n | 11 | "doi_status": true, |
12 | "domain": "https://service.tib.eu/ldmservice", | 12 | "domain": "https://service.tib.eu/ldmservice", | ||
13 | "extra_authors": [ | 13 | "extra_authors": [ | ||
14 | { | 14 | { | ||
15 | "extra_author": "Ding Liang", | 15 | "extra_author": "Ding Liang", | ||
16 | "orcid": "" | 16 | "orcid": "" | ||
17 | }, | 17 | }, | ||
18 | { | 18 | { | ||
19 | "extra_author": "Shi Yan", | 19 | "extra_author": "Shi Yan", | ||
20 | "orcid": "" | 20 | "orcid": "" | ||
21 | }, | 21 | }, | ||
22 | { | 22 | { | ||
23 | "extra_author": "Dagui Chen", | 23 | "extra_author": "Dagui Chen", | ||
24 | "orcid": "" | 24 | "orcid": "" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "extra_author": "Yu Qiao", | 27 | "extra_author": "Yu Qiao", | ||
28 | "orcid": "" | 28 | "orcid": "" | ||
29 | }, | 29 | }, | ||
30 | { | 30 | { | ||
31 | "extra_author": "Junjie Yan", | 31 | "extra_author": "Junjie Yan", | ||
32 | "orcid": "" | 32 | "orcid": "" | ||
33 | } | 33 | } | ||
34 | ], | 34 | ], | ||
35 | "groups": [ | 35 | "groups": [ | ||
36 | { | 36 | { | ||
37 | "description": "", | 37 | "description": "", | ||
38 | "display_name": "Scene Text Detection", | 38 | "display_name": "Scene Text Detection", | ||
39 | "id": "6b924d4a-92f7-46f2-b276-0f9fde3ee3a6", | 39 | "id": "6b924d4a-92f7-46f2-b276-0f9fde3ee3a6", | ||
40 | "image_display_url": "", | 40 | "image_display_url": "", | ||
41 | "name": "scene-text-detection", | 41 | "name": "scene-text-detection", | ||
42 | "title": "Scene Text Detection" | 42 | "title": "Scene Text Detection" | ||
43 | }, | 43 | }, | ||
44 | { | 44 | { | ||
45 | "description": "", | 45 | "description": "", | ||
46 | "display_name": "Scene Text Recognition", | 46 | "display_name": "Scene Text Recognition", | ||
47 | "id": "46bf41c5-757a-4706-bfc6-0dd9adf9e02e", | 47 | "id": "46bf41c5-757a-4706-bfc6-0dd9adf9e02e", | ||
48 | "image_display_url": "", | 48 | "image_display_url": "", | ||
49 | "name": "scene-text-recognition", | 49 | "name": "scene-text-recognition", | ||
50 | "title": "Scene Text Recognition" | 50 | "title": "Scene Text Recognition" | ||
51 | } | 51 | } | ||
52 | ], | 52 | ], | ||
53 | "id": "f4e51e3e-909c-4ea9-b3f0-f8d84f6bebc2", | 53 | "id": "f4e51e3e-909c-4ea9-b3f0-f8d84f6bebc2", | ||
54 | "isopen": false, | 54 | "isopen": false, | ||
55 | "landing_page": "https://github.com/xhzdeng/stela", | 55 | "landing_page": "https://github.com/xhzdeng/stela", | ||
56 | "license_title": null, | 56 | "license_title": null, | ||
57 | "link_orkg": "", | 57 | "link_orkg": "", | ||
58 | "metadata_created": "2024-12-16T18:40:52.005686", | 58 | "metadata_created": "2024-12-16T18:40:52.005686", | ||
n | 59 | "metadata_modified": "2024-12-16T18:40:52.005691", | n | 59 | "metadata_modified": "2024-12-16T18:40:52.397466", |
60 | "name": "icdar-2017-mlt", | 60 | "name": "icdar-2017-mlt", | ||
61 | "notes": "ICDAR 2017 MLT is a large scale multi-lingual text | 61 | "notes": "ICDAR 2017 MLT is a large scale multi-lingual text | ||
62 | dataset, which includes 7200 training images, 1800 validation images | 62 | dataset, which includes 7200 training images, 1800 validation images | ||
63 | and 9000 testing images. The dataset is composed of complete scene | 63 | and 9000 testing images. The dataset is composed of complete scene | ||
64 | images which come from 9 languages, and text regions in this dataset | 64 | images which come from 9 languages, and text regions in this dataset | ||
65 | can be in arbitrary orientations.", | 65 | can be in arbitrary orientations.", | ||
n | 66 | "num_resources": 0, | n | 66 | "num_resources": 1, |
67 | "num_tags": 6, | 67 | "num_tags": 6, | ||
68 | "organization": { | 68 | "organization": { | ||
69 | "approval_status": "approved", | 69 | "approval_status": "approved", | ||
70 | "created": "2024-11-25T12:11:38.292601", | 70 | "created": "2024-11-25T12:11:38.292601", | ||
71 | "description": "", | 71 | "description": "", | ||
72 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 72 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
73 | "image_url": "", | 73 | "image_url": "", | ||
74 | "is_organization": true, | 74 | "is_organization": true, | ||
75 | "name": "no-organization", | 75 | "name": "no-organization", | ||
76 | "state": "active", | 76 | "state": "active", | ||
77 | "title": "No Organization", | 77 | "title": "No Organization", | ||
78 | "type": "organization" | 78 | "type": "organization" | ||
79 | }, | 79 | }, | ||
80 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 80 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
81 | "private": false, | 81 | "private": false, | ||
82 | "relationships_as_object": [], | 82 | "relationships_as_object": [], | ||
83 | "relationships_as_subject": [], | 83 | "relationships_as_subject": [], | ||
t | 84 | "resources": [], | t | 84 | "resources": [ |
85 | { | ||||
86 | "cache_last_updated": null, | ||||
87 | "cache_url": null, | ||||
88 | "created": "2024-12-16T18:25:36", | ||||
89 | "data": [ | ||||
90 | "dcterms:title", | ||||
91 | "dcterms:accessRights", | ||||
92 | "dcterms:creator", | ||||
93 | "dcterms:description", | ||||
94 | "dcterms:issued", | ||||
95 | "dcterms:language", | ||||
96 | "dcterms:identifier", | ||||
97 | "dcat:theme", | ||||
98 | "dcterms:type", | ||||
99 | "dcat:keyword", | ||||
100 | "dcat:landingPage", | ||||
101 | "dcterms:hasVersion", | ||||
102 | "dcterms:format", | ||||
103 | "mls:task", | ||||
104 | "datacite:isDescribedBy" | ||||
105 | ], | ||||
106 | "description": "The json representation of the dataset with its | ||||
107 | distributions based on DCAT.", | ||||
108 | "format": "JSON", | ||||
109 | "hash": "", | ||||
110 | "id": "d5ea97c2-9511-4205-ab0b-f41e08a87a54", | ||||
111 | "last_modified": "2024-12-16T18:40:52.389574", | ||||
112 | "metadata_modified": "2024-12-16T18:40:52.400332", | ||||
113 | "mimetype": "application/json", | ||||
114 | "mimetype_inner": null, | ||||
115 | "name": "Original Metadata", | ||||
116 | "package_id": "f4e51e3e-909c-4ea9-b3f0-f8d84f6bebc2", | ||||
117 | "position": 0, | ||||
118 | "resource_type": null, | ||||
119 | "size": 996, | ||||
120 | "state": "active", | ||||
121 | "url": | ||||
122 | resource/d5ea97c2-9511-4205-ab0b-f41e08a87a54/download/metadata.json", | ||||
123 | "url_type": "upload" | ||||
124 | } | ||||
125 | ], | ||||
85 | "services_used_list": "", | 126 | "services_used_list": "", | ||
86 | "state": "active", | 127 | "state": "active", | ||
87 | "tags": [ | 128 | "tags": [ | ||
88 | { | 129 | { | ||
89 | "display_name": "multi-lingual", | 130 | "display_name": "multi-lingual", | ||
90 | "id": "54e6c073-7e9d-4431-bc33-5b7dd356721d", | 131 | "id": "54e6c073-7e9d-4431-bc33-5b7dd356721d", | ||
91 | "name": "multi-lingual", | 132 | "name": "multi-lingual", | ||
92 | "state": "active", | 133 | "state": "active", | ||
93 | "vocabulary_id": null | 134 | "vocabulary_id": null | ||
94 | }, | 135 | }, | ||
95 | { | 136 | { | ||
96 | "display_name": "multi-oriented text", | 137 | "display_name": "multi-oriented text", | ||
97 | "id": "039122ca-72ae-4d4c-96d6-8a300c802c60", | 138 | "id": "039122ca-72ae-4d4c-96d6-8a300c802c60", | ||
98 | "name": "multi-oriented text", | 139 | "name": "multi-oriented text", | ||
99 | "state": "active", | 140 | "state": "active", | ||
100 | "vocabulary_id": null | 141 | "vocabulary_id": null | ||
101 | }, | 142 | }, | ||
102 | { | 143 | { | ||
103 | "display_name": "natural images", | 144 | "display_name": "natural images", | ||
104 | "id": "20ae4758-7543-470f-8dc6-a950989d6516", | 145 | "id": "20ae4758-7543-470f-8dc6-a950989d6516", | ||
105 | "name": "natural images", | 146 | "name": "natural images", | ||
106 | "state": "active", | 147 | "state": "active", | ||
107 | "vocabulary_id": null | 148 | "vocabulary_id": null | ||
108 | }, | 149 | }, | ||
109 | { | 150 | { | ||
110 | "display_name": "reading competition", | 151 | "display_name": "reading competition", | ||
111 | "id": "3b40bb59-4fc0-4b28-86c4-f01e31466a3d", | 152 | "id": "3b40bb59-4fc0-4b28-86c4-f01e31466a3d", | ||
112 | "name": "reading competition", | 153 | "name": "reading competition", | ||
113 | "state": "active", | 154 | "state": "active", | ||
114 | "vocabulary_id": null | 155 | "vocabulary_id": null | ||
115 | }, | 156 | }, | ||
116 | { | 157 | { | ||
117 | "display_name": "scene text", | 158 | "display_name": "scene text", | ||
118 | "id": "2e501b26-1586-4343-bb2d-32817249e761", | 159 | "id": "2e501b26-1586-4343-bb2d-32817249e761", | ||
119 | "name": "scene text", | 160 | "name": "scene text", | ||
120 | "state": "active", | 161 | "state": "active", | ||
121 | "vocabulary_id": null | 162 | "vocabulary_id": null | ||
122 | }, | 163 | }, | ||
123 | { | 164 | { | ||
124 | "display_name": "scene text detection", | 165 | "display_name": "scene text detection", | ||
125 | "id": "fa40623b-9b38-488c-9a96-f7cf3db08503", | 166 | "id": "fa40623b-9b38-488c-9a96-f7cf3db08503", | ||
126 | "name": "scene text detection", | 167 | "name": "scene text detection", | ||
127 | "state": "active", | 168 | "state": "active", | ||
128 | "vocabulary_id": null | 169 | "vocabulary_id": null | ||
129 | } | 170 | } | ||
130 | ], | 171 | ], | ||
131 | "title": "ICDAR 2017 MLT", | 172 | "title": "ICDAR 2017 MLT", | ||
132 | "type": "dataset", | 173 | "type": "dataset", | ||
133 | "version": "" | 174 | "version": "" | ||
134 | } | 175 | } |