
# LVIS
### Dataset Summary

This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information. 

- https://www.lvisdataset.org/

### Loading
This code returns train, validation and test generators.

```python
from datasets import load_dataset

dataset = load_dataset("winvoker/lvis")
```

Objects is a dictionary which contains annotation information like bbox, class.
```
DatasetDict({
    train: Dataset({
        features: ['id', 'image', 'height', 'width', 'objects'],
        num_rows: 100170
    })
    validation: Dataset({
        features: ['id', 'image', 'height', 'width', 'objects'],
        num_rows: 4809
    })
    test: Dataset({
        features: ['id', 'image', 'height', 'width', 'objects'],
        num_rows: 19822
    })
})
```
### Access Generators
```python
train = dataset["train"]
validation = dataset["validation"]
test = dataset["test"] 
```

An example row is as follows.

```json
{  'id': 0, 
   'image': '000000437561.jpg', 
   'height': 480, 
   'width': 640, 
   'objects': {
               'bboxes': [[[392, 271, 14, 3]], 
               'classes': [117], 
               'segmentation': [[376, 272, 375, 270, 372, 269, 371, 269, 373, 269, 373]]
               }
 }
```
task_categories:image-segmentation task_ids:instance-segmentation size_categories:1M<n<10M license:cc-by-4.0 segmentation coco region:us
{"annotations_creators": [], "language_creators": [], "language": [], "license": ["cc-by-4.0"], "size_categories": ["1M<n<10M"], "source_datasets": [], "task_categories": ["image-segmentation"], "task_ids": ["instance-segmentation"], "pretty_name": "lvis", "viewer": true, "tags": ["segmentation", "coco"]}
TAGS
#task_categories-image-segmentation #task_ids-instance-segmentation #size_categories-1M<n<10M #license-cc-by-4.0 #segmentation #coco #region-us 


# LVIS
### Dataset Summary

This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information. 

- URL

### Loading
This code returns train, validation and test generators.



Objects is a dictionary which contains annotation information like bbox, class.

### Access Generators


An example row is as follows.


# LVIS ### Dataset Summary

This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information. 

- URL ### Loading
This code returns train, validation and test generators.



Objects is a dictionary which contains annotation information like bbox, class. ### Access Generators


An example row is as follows.
TAGS
#task_categories-image-segmentation #task_ids-instance-segmentation #size_categories-1M<n<10M #license-cc-by-4.0 #segmentation #coco #region-us 
 # LVIS ### Dataset Summary

This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information. 

- URL ### Loading
This code returns train, validation and test generators.



Objects is a dictionary which contains annotation information like bbox, class. ### Access Generators


An example row is as follows.
passage: TAGS
#task_categories-image-segmentation #task_ids-instance-segmentation #size_categories-1M<n<10M #license-cc-by-4.0 #segmentation #coco #region-us 
# LVIS### Dataset Summary

This dataset is the implementation of LVIS dataset into Hugging Face datasets. Please visit the original website for more information. 

- URL### Loading
This code returns train, validation and test generators.



Objects is a dictionary which contains annotation information like bbox, class.### Access Generators


An example row is as follows.