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Introducing New Image Annotation Types

by Alexandr Wang on February 9th 2017

We’re excited to be launching a bunch of new annotation types for images. Since the launch of our bounding box API, we’ve annotated millions of images with boxes to identify a host of different objects, from cars and hats to roof damage and parking lots. Scale is becoming an industry-standard tool for solving computer vision problems. We’re committed to offering developers all the tools they need. We’ve gotten many requests for a variety of image labeling types beyond boxes, and wanted to begin rolling out new labeling types to our entire community. So, we’ll be releasing the following labeling types to all customers today:

  • Pixel-wise Semantic Segmentation
  • Polygon Annotations
  • Point Annotations
  • Line Annotations
  • Pixel-wise Semantic Segmentation

import scaleapi

client = scaleapi.ScaleClient('test_6caca11856814b3128e17c74767d6d0a')

client.create_segmentannotation_task(
    callback_url='http://www.example.com/callback',
    instruction='Please segment the image using the given labels.',
    attachment_type='image',
    attachment='http://i.imgur.com/XOJbalC.jpg',
    labels=['vehicle', 'background', 'road', 'vegetation', 'lane marking'],
    allow_unlabeled=False
)

Polygon Annotation

import scaleapi

client = scaleapi.ScaleClient('test_6caca11856814b3128e17c74767d6d0a')

client.create_polygonannotation_task(
    callback_url='http://www.example.com/callback',
    instruction='Draw a tight polygon around every **car** in the image.',
    attachment_type='image',
    attachment='http://i.imgur.com/XOJbalC.jpg',
    objects_to_annotate=['car', 'truck'],
    with_labels=True
)

Line Annotation

import scaleapi

client = scaleapi.ScaleClient('test_6caca11856814b3128e17c74767d6d0a')

client.create_lineannotation_task(
    callback_url='http://www.example.com/callback',
    instruction='Annotate lines over all of the **lane lines** in the street-level image.',
    attachment_type='image',
    attachment='http://i.imgur.com/XOJbalC.jpg',
    objects_to_annotate=['solid line', 'dashed line'],
    with_labels=True,
    splines=True
)

Point Annotation

import scaleapi

client = scaleapi.ScaleClient('test_6caca11856814b3128e17c74767d6d0a')

client.create_pointannotation_task(
    callback_url='http://www.example.com/callback',
    instruction='Draw a point on every **headlight** and **brakelight** of a car in the image.',
    attachment_type='image',
    attachment='http://i.imgur.com/XOJbalC.jpg',
    objects_to_annotate=['headlight', 'brakelight'],
    with_labels=True
)

If you have other feature requests or labeling types we should support, please reach out to us on our support Slack! We currently have LIDAR point cloud annotation and cuboid annotation in beta. You can get started with a free API key today!

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