yaraalaa0 commited on
Commit
732246a
Β·
verified Β·
1 Parent(s): 5853f75

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +44 -88
README.md CHANGED
@@ -1,7 +1,19 @@
1
  ---
2
- # For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
3
- # Doc / guide: https://huggingface.co/docs/hub/datasets-cards
4
- {}
 
 
 
 
 
 
 
 
 
 
 
 
5
  ---
6
 
7
  # Dataset Card for TopAir
@@ -82,91 +94,35 @@ This dataset can be used in monocular depth estimation and semantic segmentation
82
  The dataset is organized as follows:
83
 
84
  ```
85
- β”œβ”€β”€ Images (RGB Images)
86
- β”‚ β”œβ”€β”€ H_15_P_0
87
- β”‚ β”‚ β”œβ”€β”€ ClearNoon
88
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town01
89
- β”‚ β”‚ β”‚ β”‚ └── Town01.tar.gz
90
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town02
91
- β”‚ β”‚ β”‚ β”‚ └── Town02.tar.gz
92
- β”‚ β”‚ β”‚ β”œβ”€β”€ ...
93
- β”‚ β”‚ β”‚ └── Town10HD
94
- β”‚ β”‚ β”‚ └── Town10HD.tar.gz
95
- β”‚ β”‚ β”œβ”€β”€ ClearSunset
96
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town01
97
- β”‚ β”‚ β”‚ β”‚ └── Town01.tar.gz
98
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town02
99
- β”‚ β”‚ β”‚ β”‚ └── Town02.tar.gz
100
- β”‚ β”‚ β”‚ β”œβ”€β”€ ...
101
- β”‚ β”‚ β”‚ └── Town10HD
102
- β”‚ β”‚ β”‚ └── Town10HD.tar.gz
103
- β”‚ β”‚ β”œβ”€β”€ ClearNight
104
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town01
105
- β”‚ β”‚ β”‚ β”‚ └── Town01.tar.gz
106
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town02
107
- β”‚ β”‚ β”‚ β”‚ └── Town02.tar.gz
108
- β”‚ β”‚ β”‚ β”œβ”€β”€ ...
109
- β”‚ β”‚ β”‚ └── Town10HD
110
- β”‚ β”‚ β”‚ └── Town10HD.tar.gz
111
- β”‚ β”‚ β”œβ”€β”€ CloudyNoon
112
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town..
113
- β”‚ β”‚ β”‚ β”‚ └── ..
114
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town02
115
- β”‚ β”‚ β”‚ β”‚ └── Town02.tar.gz
116
- β”‚ β”‚ β”‚ β”œβ”€β”€ ...
117
- β”‚ β”‚ β”‚ └── Town10HD
118
- β”‚ β”‚ β”‚ └── Town10HD.tar.gz
119
- β”‚ β”‚ └── MidRainyNoon
120
- β”‚ β”‚ β”œβ”€β”€ Town01
121
- β”‚ β”‚ β”‚ └── Town01.tar.gz
122
- β”‚ β”‚ β”œβ”€β”€ Town02
123
- β”‚ β”‚ β”‚ └── Town02.tar.gz
124
- β”‚ β”‚ β”œβ”€β”€ ...
125
- β”‚ β”‚ └── Town10HD
126
- β”‚ β”‚ └── Town10HD.tar.gz
127
- β”‚ β”œβ”€β”€ H_15_P_45
128
- β”‚ β”‚ └── ...
129
- β”‚ β”œβ”€β”€ ...
130
- β”‚ └── H_60_P_90
131
- β”‚ └── ...
132
- β”œβ”€β”€ Seg_ID (Semantic Segmentation Annotations)
133
- β”‚ β”œβ”€β”€ H_35_P_45
134
- β”‚ β”‚ └── ClearNoon
135
- β”‚ β”‚ β”œβ”€β”€ Town01
136
- β”‚ β”‚ β”‚ └── Town01.tar.gz
137
- β”‚ β”‚ β”œβ”€β”€ Town02
138
- β”‚ β”‚ β”‚ └── Town02.tar.gz
139
- β”‚ β”‚ β”œβ”€β”€ ...
140
- β”‚ β”‚ └── Town10HD
141
- β”‚ β”‚ └── Town10HD.tar.gz
142
- β”‚ └── ...
143
- β”œβ”€β”€ Seg_Colored (Semantic Segmentation Annotations in Colors for visualization)
144
- β”‚ β”œβ”€β”€ H_15_P_0
145
- β”‚ β”‚ β”œβ”€β”€ ClearNoon
146
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town01
147
- β”‚ β”‚ β”‚ β”‚ └── Town01.tar.gz
148
- β”‚ β”‚ β”‚ β”œβ”€β”€ Town02
149
- β”‚ β”‚ β”‚ β”‚ └── Town02.tar.gz
150
- β”‚ β”‚ β”‚ β”œβ”€β”€ ...
151
- β”‚ β”‚ β”‚ └── Town10HD
152
- β”‚ β”‚ β”‚ └── Town10HD.tar.gz
153
- β”‚ β”‚ β”œβ”€β”€ H_15_P_45
154
- β”‚ β”‚ β”‚ └── ...
155
- β”‚ β”‚ β”œβ”€β”€ ...
156
- β”‚ β”‚ └── H_60_P_90
157
- β”‚ β”‚ └── ...
158
- β”‚ └── ...
159
- └── Depth (Depth Annotations)
160
- β”œβ”€β”€ H_35_P_45
161
- β”‚ └── ClearNoon
162
- β”‚ β”œβ”€β”€ Town01
163
- β”‚ β”‚ └── Town01.tar.gz
164
- β”‚ β”œβ”€β”€ Town02
165
- β”‚ β”‚ └── Town02.tar.gz
166
- β”‚ β”œβ”€β”€ ...
167
- β”‚ └── Town10HD
168
- β”‚ └── Town10HD.tar.gz
169
- └── ...
170
 
171
  ```
172
 
 
1
  ---
2
+ task_categories:
3
+ - depth-estimation
4
+ - image-segmentation
5
+ tags:
6
+ - synthetic
7
+ - airsim
8
+ - aerial
9
+ - rural
10
+ - urban
11
+ - sim2real
12
+ - uav
13
+ - dataset
14
+ - outdoor
15
+ size_categories:
16
+ - 1K<n<10K
17
  ---
18
 
19
  # Dataset Card for TopAir
 
94
  The dataset is organized as follows:
95
 
96
  ```
97
+ β”œβ”€β”€ AccuCities_1 (environmentName_trajectoryNum)
98
+ β”‚ β”œβ”€β”€ depth (depth maps annotation)
99
+ β”‚ β”œβ”€β”€ images (RGB frames)
100
+ β”‚ β”œβ”€β”€ seg_colored (segmentation maps in colors)
101
+ β”‚ β”œβ”€β”€ seg_id (segmentation maps represented with class ids)
102
+ β”‚ └── camera_loc.txt (camera locations and orientations)
103
+ β”‚
104
+ β”œβ”€β”€ AccuCities_2
105
+ β”‚ β”œβ”€β”€ depth
106
+ β”‚ β”œβ”€β”€ images
107
+ β”‚ β”œβ”€β”€ seg_colored
108
+ β”‚ β”œβ”€β”€ seg_id
109
+ β”‚ └── camera_loc.txt
110
+ β”‚
111
+ β”œβ”€β”€ AccuCities_2
112
+ β”‚ β”œβ”€β”€ depth
113
+ β”‚ β”œβ”€β”€ images
114
+ β”‚ β”œβ”€β”€ seg_colored
115
+ β”‚ β”œβ”€β”€ seg_id
116
+ β”‚ └── camera_loc.txt
117
+ β”‚
118
+ β”œβ”€β”€ ....
119
+ β”‚
120
+ └── RuralAust3_2
121
+ β”œβ”€β”€ depth
122
+ β”œβ”€β”€ images
123
+ β”œβ”€β”€ seg_colored
124
+ β”œβ”€β”€ seg_id
125
+ └── camera_loc.txt
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
126
 
127
  ```
128