Point Cloud Custom Classifier.

Your custom-made automatic point cloud classifier – trained and tested for your use case.

What the Point Cloud Custom Classifier achieves.

Manually annotating data in 3D point clouds is a very time-consuming process.

You can significantly reduce this effort of manual annotation with your own Point Cloud Custom Classifier. It offers you automated and personalized point cloud classifications with the help of AI. We train a model just for your use case to give your performance a boost and open up new possibilities.

Our clients reported that for some scenarios the classification effort could be shortened from several days (with manual annotation) to a few hours when using our Custom Classifier service.

a graph showing the advantages of the AI Training Service over manual 3d point cloud annotation

How do Point Cloud Custom Classifiers work?

You can either quickly generate training data yourself in our Pointly platform or through our labeling workforce. If you have already classified data, you can leverage it as training material for your classifier and get a jump start with our 3D Point Cloud Services.

Our team of AI experts will accompany you in this process, defining KPIs according to your needs and regularly updating you on performance.

Phase 1

To start the training of your AI model, you’ll need to upload your data to Pointly and manually classify your point clouds to generate training data for the model. As soon as you have a decent amount of training data, we can start training your custom classifier.

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Phase 2

After supplying enough input, the model can take over to classify your point clouds – you only need to make manual corrections. Through reinforcement learning, each repeated cycle of the process improves the output of your point cloud custom classifier. After doing the manual work a few times you rarely have to do it ever again.

a graphic with a gear that says that thanks to the AI Training Service the point cloud classification now runs automatically

How to get your hands on the new Point Cloud Custom Classifier

  1. Use the form below to submit your inquiry.
  2. You will receive a Pointly Professional Account to upload your point clouds. The data is split into three batches. Each batch is labeled, either by you or through our labeling workforce*. Then, we run training for each batch, optimize them automatically, and report the performance back to you.

Do you want to know more, or do you have any questions? Please read our FAQ or send us an email to sales@pointly.ai!

*Labeling fees apply at competitive rates.

What you get:

  • A Professional Pointly subscription
  • A personal consultation session with our AI experts to assess your goals and define KPIs
  • Regular performance updates on the training progress
  • A custom point cloud classifier with a trained AI, tried and tested for your use case that you can keep using and training

How it works.

Take these four main steps to get your own Custom Classifier!

1) Create a customized Class Catalog and link it to a new project.

2) Upload your .las/.laz files to the project via the Upload Dialog.

3) Now the data can be classified in Pointly to generate training data for the model. Use a Pointly Standard Classifier for automatic pre-classification and manually correct results or let us handle the task entirely for you with a Managed Workforce.

4) We train the Custom Classifier and deploy it to your Pointly Account. Now you can apply it to new data and use it for your projects. Alternatively, we can provide your classifier via an API or as On-Premises Classification Tool.

annotate objects in 3d point clouds

Point Cloud Custom Classifier FAQ.

Simply tell us about your use case in the linked form. It takes less than 3 minutes! Or send us an email to sales@pointly.ai

Once we have trained a neural network classifier for your use case, we can automatically classify new cloud data.

  • We will provide you with a Pointly Professional License. That means you can upload your point clouds into a custom project.
  • Does your data already contain labels? Great, we can start straight away with training a classifier on those.
  • Don’t worry: Pointly was built for quickly generating training data if you don’t have labeled data. You can either do it yourself or order a labeling service through us.

5-15 days of labeling work provide a realistic start for a Proof of Concept. That means you will get a solid estimate of the future potentials of AI but not yet a production-ready model. This number can, of course, vary a lot depending on your use case and the desired performance. We are offering you a briefing call where we clarify all specifics that apply to your use case. You can choose to either invest that effort yourself or hire a labeling service from us at competitive rates. Naturally, more training data is always beneficial for training the AI model.

The first and most crucial step is that you choose a test site to be put aside. We will not train on this test site but will use it to evaluate the final performance of the neural network. We will keep you updated on the current performance: based on cross-validations within the current set during the training process on the separate groups of data.

Split the available data into three evenly sized sets, beginning with the first, then adding the second, and so forth. Why this iterative approach?

  • It allows us to evaluate how performance increases with additional training data
  • It gives you more flexibility and control when generating training data.

After every iteration, we provide you a short report on the current performance.

Afterward, you can keep using your neural network for classification tasks and re-train it with more data based on standard charges.

Please fill out the form down below to inquire about an AI Training Service with us.

 


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made in Germany

Pointly is a spin-off of Supper & Supper GmbH from Germany. The company is one of the leading full-service data science service providers in the country and develops customized solutions in the areas of machine learning, artificial intelligence, process optimization and digital transformation.

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