Hugging Face's logo

Datasets:
agianbig
/
mixed_depth

Tasks:
Visual Question Answering
Depth Estimation
Modalities:
Image
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
depth
spatial-reasoning
computer-vision
multimodal
vlm
ablate-to-validate
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
1
agianbig commited on
Commit
1fbf42a
·
verified ·
1 Parent(s): bf1d4c3

Add viewer parquet (data/) with rendered images + tabular columns

Browse files
Files changed (3) hide show
  1. README.md +65 -0
  2. data/train-00000-of-00001.parquet +3 -0
  3. dataset_infos.json +134 -120
README.md CHANGED
@@ -12,6 +12,71 @@ tags:
12
  - multimodal
13
  size_categories:
14
  - 1K<n<10K
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15
  ---
16
 
17
  # Depth Point Dataset
 
12
  - multimodal
13
  size_categories:
14
  - 1K<n<10K
15
+ configs:
16
+ - config_name: default
17
+ data_files:
18
+ - split: train
19
+ path: data/train-*
20
+ dataset_info:
21
+ features:
22
+ - name: id
23
+ dtype: string
24
+ - name: image_filename
25
+ dtype: string
26
+ - name: original_image
27
+ dtype: string
28
+ - name: question
29
+ dtype: string
30
+ - name: answer
31
+ dtype: string
32
+ - name: answer_letter
33
+ dtype: string
34
+ - name: answer_type
35
+ dtype: string
36
+ - name: num_points
37
+ dtype: int64
38
+ - name: point_labels
39
+ sequence: string
40
+ - name: depth_token
41
+ dtype: string
42
+ - name: point_A_x
43
+ dtype: int64
44
+ - name: point_A_y
45
+ dtype: int64
46
+ - name: point_B_x
47
+ dtype: int64
48
+ - name: point_B_y
49
+ dtype: int64
50
+ - name: point_C_x
51
+ dtype: int64
52
+ - name: point_C_y
53
+ dtype: int64
54
+ - name: point_D_x
55
+ dtype: int64
56
+ - name: point_D_y
57
+ dtype: int64
58
+ - name: point_E_x
59
+ dtype: int64
60
+ - name: point_E_y
61
+ dtype: int64
62
+ - name: point_A_depth
63
+ dtype: float64
64
+ - name: point_B_depth
65
+ dtype: float64
66
+ - name: point_C_depth
67
+ dtype: float64
68
+ - name: point_D_depth
69
+ dtype: float64
70
+ - name: point_E_depth
71
+ dtype: float64
72
+ - name: image
73
+ dtype: image
74
+ splits:
75
+ - name: train
76
+ num_bytes: 466678289.0
77
+ num_examples: 19279
78
+ download_size: 421666211
79
+ dataset_size: 466678289.0
80
  ---
81
 
82
  # Depth Point Dataset
data/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7804b4e2ea7c89ab639ed1e43d8c87ed4e662c64992503df70d7113fd4f3fc78
3
+ size 421666211
dataset_infos.json CHANGED
@@ -1,122 +1,136 @@
1
  {
2
- "default": {
3
- "description": "Depth-based question-answer pairs for vision-language models",
4
- "features": {
5
- "id": {
6
- "_type": "Value",
7
- "dtype": "string"
8
- },
9
- "image": {
10
- "_type": "Image"
11
- },
12
- "image_filename": {
13
- "_type": "Value",
14
- "dtype": "string"
15
- },
16
- "original_image": {
17
- "_type": "Value",
18
- "dtype": "string"
19
- },
20
- "question": {
21
- "_type": "Value",
22
- "dtype": "string"
23
- },
24
- "answer": {
25
- "_type": "Value",
26
- "dtype": "string"
27
- },
28
- "answer_letter": {
29
- "_type": "Value",
30
- "dtype": "string"
31
- },
32
- "answer_type": {
33
- "_type": "Value",
34
- "dtype": "string"
35
- },
36
- "num_points": {
37
- "_type": "Value",
38
- "dtype": "int32"
39
- },
40
- "point_labels": {
41
- "_type": "Sequence",
42
- "feature": {
43
- "_type": "Value",
44
- "dtype": "string"
45
- }
46
- },
47
- "depth_token": {
48
- "_type": "Value",
49
- "dtype": "string"
50
- },
51
- "point_A_x": {
52
- "_type": "Value",
53
- "dtype": "float32"
54
- },
55
- "point_A_y": {
56
- "_type": "Value",
57
- "dtype": "float32"
58
- },
59
- "point_A_depth": {
60
- "_type": "Value",
61
- "dtype": "float32"
62
- },
63
- "point_B_x": {
64
- "_type": "Value",
65
- "dtype": "float32"
66
- },
67
- "point_B_y": {
68
- "_type": "Value",
69
- "dtype": "float32"
70
- },
71
- "point_B_depth": {
72
- "_type": "Value",
73
- "dtype": "float32"
74
- },
75
- "point_C_x": {
76
- "_type": "Value",
77
- "dtype": "float32"
78
- },
79
- "point_C_y": {
80
- "_type": "Value",
81
- "dtype": "float32"
82
- },
83
- "point_C_depth": {
84
- "_type": "Value",
85
- "dtype": "float32"
86
- },
87
- "point_D_x": {
88
- "_type": "Value",
89
- "dtype": "float32"
90
- },
91
- "point_D_y": {
92
- "_type": "Value",
93
- "dtype": "float32"
94
- },
95
- "point_D_depth": {
96
- "_type": "Value",
97
- "dtype": "float32"
98
- },
99
- "point_E_x": {
100
- "_type": "Value",
101
- "dtype": "float32"
102
- },
103
- "point_E_y": {
104
- "_type": "Value",
105
- "dtype": "float32"
106
- },
107
- "point_E_depth": {
108
- "_type": "Value",
109
- "dtype": "float32"
110
- }
111
- },
112
- "splits": {
113
- "train": {
114
- "name": "train",
115
- "num_examples": 19279,
116
- "dataset_name": "ade20k_depth_discrete_long_only"
117
- }
118
- },
119
- "license": "mit",
120
- "homepage": ""
121
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
122
  }
 
1
  {
2
+ "default": {
3
+ "description": "",
4
+ "citation": "",
5
+ "homepage": "",
6
+ "license": "",
7
+ "features": {
8
+ "id": {
9
+ "dtype": "string",
10
+ "_type": "Value"
11
+ },
12
+ "image_filename": {
13
+ "dtype": "string",
14
+ "_type": "Value"
15
+ },
16
+ "original_image": {
17
+ "dtype": "string",
18
+ "_type": "Value"
19
+ },
20
+ "question": {
21
+ "dtype": "string",
22
+ "_type": "Value"
23
+ },
24
+ "answer": {
25
+ "dtype": "string",
26
+ "_type": "Value"
27
+ },
28
+ "answer_letter": {
29
+ "dtype": "string",
30
+ "_type": "Value"
31
+ },
32
+ "answer_type": {
33
+ "dtype": "string",
34
+ "_type": "Value"
35
+ },
36
+ "num_points": {
37
+ "dtype": "int64",
38
+ "_type": "Value"
39
+ },
40
+ "point_labels": {
41
+ "feature": {
42
+ "dtype": "string",
43
+ "_type": "Value"
44
+ },
45
+ "_type": "Sequence"
46
+ },
47
+ "depth_token": {
48
+ "dtype": "string",
49
+ "_type": "Value"
50
+ },
51
+ "point_A_x": {
52
+ "dtype": "int64",
53
+ "_type": "Value"
54
+ },
55
+ "point_A_y": {
56
+ "dtype": "int64",
57
+ "_type": "Value"
58
+ },
59
+ "point_B_x": {
60
+ "dtype": "int64",
61
+ "_type": "Value"
62
+ },
63
+ "point_B_y": {
64
+ "dtype": "int64",
65
+ "_type": "Value"
66
+ },
67
+ "point_C_x": {
68
+ "dtype": "int64",
69
+ "_type": "Value"
70
+ },
71
+ "point_C_y": {
72
+ "dtype": "int64",
73
+ "_type": "Value"
74
+ },
75
+ "point_D_x": {
76
+ "dtype": "int64",
77
+ "_type": "Value"
78
+ },
79
+ "point_D_y": {
80
+ "dtype": "int64",
81
+ "_type": "Value"
82
+ },
83
+ "point_E_x": {
84
+ "dtype": "int64",
85
+ "_type": "Value"
86
+ },
87
+ "point_E_y": {
88
+ "dtype": "int64",
89
+ "_type": "Value"
90
+ },
91
+ "point_A_depth": {
92
+ "dtype": "float64",
93
+ "_type": "Value"
94
+ },
95
+ "point_B_depth": {
96
+ "dtype": "float64",
97
+ "_type": "Value"
98
+ },
99
+ "point_C_depth": {
100
+ "dtype": "float64",
101
+ "_type": "Value"
102
+ },
103
+ "point_D_depth": {
104
+ "dtype": "float64",
105
+ "_type": "Value"
106
+ },
107
+ "point_E_depth": {
108
+ "dtype": "float64",
109
+ "_type": "Value"
110
+ },
111
+ "image": {
112
+ "_type": "Image"
113
+ }
114
+ },
115
+ "builder_name": "parquet",
116
+ "dataset_name": "parquet",
117
+ "config_name": "default",
118
+ "version": {
119
+ "version_str": "0.0.0",
120
+ "major": 0,
121
+ "minor": 0,
122
+ "patch": 0
123
+ },
124
+ "splits": {
125
+ "train": {
126
+ "name": "train",
127
+ "num_bytes": 466678289.0,
128
+ "num_examples": 19279,
129
+ "dataset_name": "mixed_depth"
130
+ }
131
+ },
132
+ "download_size": 421666211,
133
+ "dataset_size": 466678289.0,
134
+ "size_in_bytes": 888344500.0
135
+ }
136
  }