File size: 3,329 Bytes
0f37849
634ec99
0f37849
 
 
 
 
 
b18cd6a
 
e67045c
 
 
 
 
 
 
0f37849
e67045c
0f37849
e67045c
0f37849
e67045c
0f37849
 
 
595ecd7
0f37849
 
595ecd7
0f37849
595ecd7
 
0f37849
 
 
 
 
 
 
80b094a
 
0f37849
 
 
1255ccb
 
0f37849
 
 
 
 
 
 
 
 
 
 
f8e61eb
0f37849
 
 
 
59f6ae9
 
0f37849
 
 
5506679
0f37849
 
 
 
 
ad2996a
 
0f37849
 
8529e60
0f37849
8da8d8e
 
0f37849
 
 
8529e60
5adc2db
 
 
634ec99
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
---
license: odc-by
dataset_info:
  features:
  - name: example_id
    dtype: string
  - name: watchface_id
    dtype: string
  - name: watchface_name
    dtype: string
  - name: watch_time
    dtype: string
  - name: time_format
    dtype: string
  - name: shows_seconds
    dtype: bool
  - name: hour_visible
    dtype: int32
  - name: minute_visible
    dtype: int32
  - name: second_visible
    dtype: int32
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 130732460
    num_examples: 800269
  - name: validation
    num_bytes: 4180551
    num_examples: 25600
  download_size: 69712029
  dataset_size: 134913011
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
task_categories:
- visual-question-answering
---

# PixMo-Clocks
PixMo-Clocks is a collection of virtual watch faces and time annotations. 
The repo supplies the meta-data needed to build the data but does not directly contain the images, which are from facer.io.

PixMo-Clocks is a part of the PixMo dataset collection and was used to train the [Molmo family of models](https://huggingface.co/collections/allenai/molmo-66f379e6fe3b8ef090a8ca19)

Quick links:
- 📃 [Paper](https://molmo.allenai.org/paper.pdf)
- 🎥 [Blog with Videos](https://molmo.allenai.org/blog)


## Loading

```python
data = datasets.load_dataset("allenai/pixmo-clocks", split="train")
```

## Data Format
The data includes:
- `watchface_id`: The watchface id to use to generate the image
- `watchface_name`: The name of the watchface used
- `watch_time`: The time the watch was set to, not all the details of the time will be visible on the watchface, so the
the following two fields are needed.
- `time_format`: The format of the watch, can be:
  - `"No time visible`": The time cannot be read at all, we still include these examples as no-answer training examples
  - `"Without AM/PM`": AM/PM cannot be determined
  - `"With AM/PM`": AM/PM can be determined (either because the watch shows military time, or shows a AM/PM indicator somehow)
- `shows_seconds`: Whether seconds are shown

For convenience, this dataset includes a few fields derived from this data about what is visible on the watch:
- `hour_visible`: The hour visible on the watch, between 0 and 23, -1 means not visible, 0 is 12:00am.
  If AM/PM cannot be determined the hour will be between 0 and 11
- `minute_visible`: The minute the watch should be set to, between 0 and 59, -1 means not visible
- `second_visible`: The second the watch should be set to, between -1 and 59, -1 means not visible
- `text`: A text string of the time visible on the watch

## Downloading Images
Downloading the images requires downloading the watch face set to the correct time from facer.io.
We will include a script to generate the images as part of our code release.

## Splits
The data is divided into validation and train splits. These splits are unofficial because we do not use this data for evaluation anyway. However,
they reflect what was used when training the Molmo models, which were only trained on the train split.

## License
This dataset is licensed under ODC-BY-1.0. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).