Academy
Docs
- New dataset
- New organization
Sign in

saptadeb /

Corn

Public

Image

Segmentation

Overview
Samples
Issues
Releases

32%

Label set

ground-truth

Create a new label set

A label set is a collection of labels. Create a new label set if you want to upload model predictions and use features such as model-assisted labeling.

Name

Description (optional)

Set up the SDK

From the command line, install the Segments.ai Python SDK.

pip install --upgrade segments-ai

Initialize the Segments client using your API key.

from segments import SegmentsClient

...api_key = ""

client = SegmentsClient(api_key)

Copy the code block using the button to obtain your full API key.

Create a new label set

Create a new label set with client.add_labelset(). You need to specify the name and (optionally) the description of the new label set.

dataset_identifier = "saptadeb/Corn"
name = "model-predictions"

client.add_labelset(dataset_identifier, name)

Search syntax

This is an example dataset

For best performance, create a new dataset and choose a suitable data category.

Upload errors

frames_05_24_2021_15_43_25_rgb_10021.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10051.jpg

5 years ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10081.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10111.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10141.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10171.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10201.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_1021.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10231.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10261.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10291.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10321.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10351.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10381.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10411.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10441.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10471.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10501.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_1051.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10531.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10561.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10591.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10621.jpg

5 years ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10651.jpg

8 months ago

Reviewed

frames_05_24_2021_15_43_25_rgb_10681.jpg

8 months ago

Reviewed

Add samples

Click to select files
or drag and drop files

.jpg, .png

Set up the SDK

From the command line, install the Segments.ai Python SDK.

pip install --upgrade segments-ai

Initialize the Segments client using your API key.

from segments import SegmentsClient

...api_key = ""

client = SegmentsClient(api_key)

Copy the code block using the button to obtain your full API key.

Upload a file

Use client.upload_asset() to upload a local file to Segments.ai's asset storage service.

filename = "shiba_inu_178.jpg"

with open(f"path/to/{filename}", "rb") as f:
    asset = client.upload_asset(f, filename=filename)

image_url = asset.url

Add a sample

Add a sample with client.add_sample(). For each sample, specify a name and the required sample attributes. If you do not have URLs for your assets, upload the assets to Segments.ai first.

dataset = "saptadeb/Corn"

name = "shiba_inu_178"

image_url = "https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/jane/4f47973f-5568-47f1-8a7d-44bfeb6f0f76.jpg"
attributes = {"image": {"url": image_url}}

sample = client.add_sample(dataset, name, attributes)

Set the point cloud types

Are you sure you want to delete this label set? All labels in the label set will be deleted as well.

Are you sure you want to delete 0 samples? The corresponding labels will be deleted as well.