chunked/nltk_chunking/tasks_object_detection/chunk_30.txt

Apply the same approach here, resize each image to (480, 480),
flip it horizontally, and brighten it:

import albumentations
import numpy as np
import torch
transform = albumentations.Compose(
     [
         albumentations.Resize(480, 480),
         albumentations.HorizontalFlip(p=1.0),
         albumentations.RandomBrightnessContrast(p=1.0),
     ],
     bbox_params=albumentations.BboxParams(format="coco", label_fields=["category"]),
 )

The image_processor expects the annotations to be in the following format: {'image_id': int, 'annotations': List[Dict]},
 where each dictionary is a COCO object annotation.