---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: mask
    dtype: image
  splits:
  - name: train
    num_bytes: 547096711
    num_examples: 5000
  - name: validation
    num_bytes: 117520888
    num_examples: 1000
  - name: test
    num_bytes: 496235957.648
    num_examples: 4428
  download_size: 1184441980
  dataset_size: 1160853556.648
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
license: apache-2.0
task_categories:
- image-segmentation
size_categories:
- 1K<n<10K
---

# Links
* Paper: https://arxiv.org/pdf/2101.08461
* Repository: https://github.com/xieenze/Trans2Seg

# Dataset composition
There might be some differences with what the paper describes.  We try to investigate and get this unique colors in the mask images:

```
Color (np.uint32(0), np.uint32(0), np.uint32(0)): Found in 10428 images
Color (np.uint32(235), np.uint32(255), np.uint32(7)): Found in 997 images
Color (np.uint32(255), np.uint32(51), np.uint32(7)): Found in 3313 images
Color (np.uint32(120), np.uint32(120), np.uint32(120)): Found in 1572 images
Color (np.uint32(224), np.uint32(5), np.uint32(255)): Found in 3059 images
Color (np.uint32(150), np.uint32(5), np.uint32(61)): Found in 1472 images
Color (np.uint32(204), np.uint32(5), np.uint32(255)): Found in 340 images
Color (np.uint32(4), np.uint32(250), np.uint32(7)): Found in 603 images
Color (np.uint32(204), np.uint32(255), np.uint32(4)): Found in 501 images
Color (np.uint32(140), np.uint32(140), np.uint32(140)): Found in 410 images
Color (np.uint32(120), np.uint32(120), np.uint32(70)): Found in 279 images
Color (np.uint32(6), np.uint32(230), np.uint32(230)): Found in 90 images
Color (np.uint32(255), np.uint32(0), np.uint32(0)): Found in 1 images # red, this is a cup, mapped to (255, 51, 7)
```

| Index | Class Name | Image Count (from paper) | Closest Color Count | Ordered RGB Value |
| :--- | :--- | :--- | :--- | :--- |
| 0 | `background` | (not listed) | 10428 | `[0, 0, 0]` |
| 1 | `box` | 603 | 603 | `[4, 250, 7]` |
| 2 | `bottle` | 1472 | 1472 | `[150, 5, 61]` |
| 3 | `window` | 501 | 501 | `[204, 255, 4]` |
| 4 | `eyeglass` | 410 | 410 | `[140, 140, 140]` |
| 5 | `freezer` | 90 | 90 | `[6, 230, 230]` |
| 6 | `jar/kettle` | 997 | 997 | `[235, 255, 7]` |
| 7 | `door` | 1572 | 1572 | `[120, 120, 120]` |
| 8 | `cup` | 3315 | 3313+1 | `[255, 51, 7]` |
| 9 | `wall` | 3059 | 3059 | `[224, 5, 255]` |
| 10 | `bowl` | 340 | 340 | `[204, 5, 255]` |
| 11 | `shelf` | 280 | 279 | `[120, 120, 70]` |

# Split info
We use the same split composition as the original dataset.

# License info
We attach Apaceh 2.0 license as it is the license used in the github repository, please look up to the paper and the repository for better details.