using_pycocotools
How to use Pycocotools and CocoDataset. Pycocotools detailed explanation.
What is COCO?
COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features:
- Object segmentation
- Recognition in context
- Superpixel stuff segmentation
- 330K images (>200K labeled)
- 1.5 million object instances
- 80 object categories
- 91 stuff categories
- 5 captions per image
- 250,000 people with keypoints
COCO Dataset Formats
Images: Provides all the image information in the dataset without bounding box or segmentation information. An example of image information
“image”: [{'license': 4,
'file_name': '000000252219.jpg',
'coco_url': 'http://images.cocodataset.org/val2017/000000252219.jpg',
'height': 428,
'width': 640,
'date_captured': '2013-11-14 22:32:02',
'flickr_url': 'http://farm4.staticflickr.com/3446/3232237447_13d84bd0a1_z.jpg',
'id': 252219
}]
Annotations: Provides a list of every individual object annotation from each image in the dataset.
anns [
{'segmentation': [[361.81, …, 365.48]],
'num_keypoints': 17,
'area': 8511.1568,
'iscrowd': 0,
'keypoints': [356, 198, 2, …, 355, 354, 2],
'image_id': 252219,
'bbox': [326.28, 174.56, 71.24, 197.25],
'category_id': 1,
'id': 481918},
…
]