from sahi.utils.coco import Coco
# init Coco object
coco = Coco.from_coco_dict_or_path("coco.json")
# get dataset stats
coco.stats
{
'num_images': 6471,
'num_annotations': 343204,
'num_categories': 2,
'num_negative_images': 0,
'num_images_per_category': {'human': 5684, 'vehicle': 6323},
'num_annotations_per_category': {'human': 106396, 'vehicle': 236808},
'min_num_annotations_in_image': 1,
'max_num_annotations_in_image': 902,
'avg_num_annotations_in_image': 53.037243084530985,
'min_annotation_area': 3,
'max_annotation_area': 328640,
'avg_annotation_area': 2448.405738278109,
'min_annotation_area_per_category': {'human': 3, 'vehicle': 3},
'max_annotation_area_per_category': {'human': 72670, 'vehicle': 328640},
}
- add category based annotation area filtering (#86):
# filter out images with seperate area intervals per category
intervals_per_category = {
"human": {"min": 20, "max": 10000},
"vehicle": {"min": 50, "max": 15000},
}
area_filtered_coco = coco.get_area_filtered_coco(intervals_per_category=intervals_per_category)
