Francesco commited on
Commit
d807d10
1 Parent(s): 35a593c

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +110 -14
README.md CHANGED
@@ -26,19 +26,115 @@ dataset_info:
26
  '1': Minorrotation
27
  '2': Moderaterotation
28
  '3': Severerotation
29
- splits:
30
- - name: train
31
- num_bytes: 9795912.0
32
- num_examples: 325
33
- - name: validation
34
- num_bytes: 1302361.0
35
- num_examples: 40
36
- - name: test
37
- num_bytes: 2969639.0
38
- num_examples: 96
39
- download_size: 14071497
40
- dataset_size: 14067912.0
 
 
 
 
 
 
 
 
41
  ---
42
- # Dataset Card for "wall-damage"
43
 
44
- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
26
  '1': Minorrotation
27
  '2': Moderaterotation
28
  '3': Severerotation
29
+ annotations_creators:
30
+ - crowdsourced
31
+ language_creators:
32
+ - found
33
+ language:
34
+ - en
35
+ license:
36
+ - cc
37
+ multilinguality:
38
+ - monolingual
39
+ size_categories:
40
+ - 1K<n<10K
41
+ source_datasets:
42
+ - original
43
+ task_categories:
44
+ - object-detection
45
+ task_ids: []
46
+ pretty_name: wall-damage
47
+ tags:
48
+ - rf100
49
  ---
 
50
 
51
+ # Dataset Card for wall-damage
52
+
53
+ ** The original COCO dataset is stored at `dataset.tar.gz`**
54
+
55
+ ## Dataset Description
56
+
57
+ - **Homepage:** https://universe.roboflow.com/object-detection/wall-damage
58
+ - **Point of Contact:** francesco.zuppichini@gmail.com
59
+
60
+ ### Dataset Summary
61
+
62
+ wall-damage
63
+
64
+ ### Supported Tasks and Leaderboards
65
+
66
+ - `object-detection`: The dataset can be used to train a model for Object Detection.
67
+
68
+ ### Languages
69
+
70
+ English
71
+
72
+ ## Dataset Structure
73
+
74
+ ### Data Instances
75
+
76
+ A data point comprises an image and its object annotations.
77
+
78
+ ```
79
+ {
80
+ 'image_id': 15,
81
+ 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
82
+ 'width': 964043,
83
+ 'height': 640,
84
+ 'objects': {
85
+ 'id': [114, 115, 116, 117],
86
+ 'area': [3796, 1596, 152768, 81002],
87
+ 'bbox': [
88
+ [302.0, 109.0, 73.0, 52.0],
89
+ [810.0, 100.0, 57.0, 28.0],
90
+ [160.0, 31.0, 248.0, 616.0],
91
+ [741.0, 68.0, 202.0, 401.0]
92
+ ],
93
+ 'category': [4, 4, 0, 0]
94
+ }
95
+ }
96
+ ```
97
+
98
+ ### Data Fields
99
+
100
+ - `image`: the image id
101
+ - `image`: `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
102
+ - `width`: the image width
103
+ - `height`: the image height
104
+ - `objects`: a dictionary containing bounding box metadata for the objects present on the image
105
+ - `id`: the annotation id
106
+ - `area`: the area of the bounding box
107
+ - `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format)
108
+ - `category`: the object's category.
109
+
110
+
111
+ #### Who are the annotators?
112
+
113
+ Annotators are Roboflow users
114
+
115
+ ## Additional Information
116
+
117
+ ### Licensing Information
118
+
119
+ See original homepage https://universe.roboflow.com/object-detection/wall-damage
120
+
121
+ ### Citation Information
122
+
123
+ ```
124
+ @misc{ wall-damage,
125
+ title = { wall damage Dataset },
126
+ type = { Open Source Dataset },
127
+ author = { Roboflow 100 },
128
+ howpublished = { \url{ https://universe.roboflow.com/object-detection/wall-damage } },
129
+ url = { https://universe.roboflow.com/object-detection/wall-damage },
130
+ journal = { Roboflow Universe },
131
+ publisher = { Roboflow },
132
+ year = { 2022 },
133
+ month = { nov },
134
+ note = { visited on 2023-03-29 },
135
+ }"
136
+ ```
137
+
138
+ ### Contributions
139
+
140
+ Thanks to [@mariosasko](https://github.com/mariosasko) for adding this dataset.