First steps with Remo python library

Create and visualize a dataset

Let's create a new dataset and upload some annotations.

import remo
import pandas as pd
remo.set_viewer('jupyter')

urls = ['https://remo-scripts.s3-eu-west-1.amazonaws.com/open_images_sample_dataset.zip']

my_dataset = remo.create_dataset(name = 'open images detection',
                    urls = urls,
                    annotation_task = "Object detection")

Acquiring data - completed
Processing data - completed
Data upload completed

You can read more about what type of annotation tasks and formats we support in the documentation.

We can easily list all datasets and retrieve one

remo.list_datasets()

[Dataset 1 - 'ocr_symbols', Dataset 2 - 'test', Dataset 8 - 'open_images', Dataset 9 - 'test', Dataset 12 - 'open images detection']

# make sure to use the right ID when running the tutorial
new_dataset = remo.get_dataset(1)

Let's visualise our dataset

my_dataset.view()

view_dataset.gif

Visualize Annotation Statistics

To explore annotations, we can print the stats of the annotation sets or open the interactive UI

my_dataset.get_annotation_statistics()

[{'AnnotationSet ID': 41, 'AnnotationSet name': 'Object detection', 'n_images': 10, 'n_classes': 18, 'n_objects': 98, 'top_3_classes': [{'name': 'Fruit', 'count': 27}, {'name': 'Sports equipment', 'count': 12}, {'name': 'Human arm', 'count': 10}], 'creation_date': None, 'last_modified_date': '2020-05-29T13:38:52.259776Z'}]

my_dataset.view_annotation_stats()

annotation_statistics.png

Export Annotations

We can easily export annotations in a standardised format, and use them for training a model or further analysis

my_dataset.export_annotations_to_file('output.csv', annotation_format='csv')

Further SDK functionalities

Refer to the other tutorials and the documentation to explore further the SDK.

Other functionalities include:

  • Manipulating annotation sets from code
  • Custom uploading of annotations, predictions and images
  • Advanced images search
  • Organising data in virtual folders