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LabelFlow: Beginners' guide to image labeling

Discover how to use the Labelflow platform in 3 minutes!

At Labelflow we build the fastest image labeling tool on the internet. The open standard image labeling tool, helping our users curate large datasets for machine learning models, and scale their AI projects

Our mission is to provide the AI community with a solution that seamlessly integrates within their software ecosystem while providing the most straightforward labeling experience.

Garbage in garbage out

Based on years of experience working in the energy space helping utility companies identifying hazards on the grids, we clearly figured out that it was possible to bring AI at scale on complex use cases, saving time and increasing reliability. There is a “BUT”, there is no secret sauce: the dataset must be large, homogeneous AND accurately labeled.

Let us take a test case to see how you can leverage LabelFlow to scale your machine learning models today!

1. Gather your dataset

Let us take the case that you are making a machine learning model that identifies rhinos from an image for wildlife protection services. You need to train your model with high-quality labeled images so you can produce an effective tool against poaching.
The first step is to gather a dataset of images containing rhinos. You can save it online or store it locally on your computer.

2. Create a project for your data set

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Navigate to LabelFlow and you will be welcomed with this interface. Press “Start Labeling”. Click on “Create new project” and give your project a name. Now press “Start Labeling” and enter your project.

3. Upload your images

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Press “Add images” and you drop all the images that you will label for this project. You can drag and drop the images onto the screen or paste the URL to your database. You can also drop the URL to your database if your images are on the cloud.

It will lead you to a gallery where you can see all your pictures.

Select the image you would like to label first and away we go!

4. Label images

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Select the bounding box tool and click on the edges of the Rhinos you would like to label. Two guiding lines will be available to help you select the edges. Right-click on the bounding box to specify the class of the label. Labels are colored by class for convenience.

Polygon_tool.png

Select the small arrow on the drawing tool and choose the polygon tool. Draw a polygon around the rhino and adjust the vertices at the end by dragging them.

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💡 Tips! You can use the different shortcuts to optimize your productivity.

Navigate between your images by simply choosing the next image you would like to label or clicking the small arrows at the bottom left.

You can also use the left and right arrow keys.

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Labels can overlap, intersect or encompass other labels. Zoom in on your images by using the top right button or by using the trackpad.

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Create as many label classes as you need.

5. Export labels

Once you are finished, select the export tool on the top right.

Export_labels.gif

This will give you a small menu with information about the number of labels and allows you to specify the export format, including COCO.

Select your desired file type and it will download to your device. Now you are ready to train your AI model! It’s that easy!

What’s next?

LabelFlow is a simple and lean tool for now, we will be super excited if you tell us here what other features would be great to support you in building your next big thing!

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