Code libraries will help users kickstart computer vision projects
Landing AI, the leading computer vision cloud platform, released updates to the Landing AI GitHub repository to help AI practitioners, whether seasoned or just starting out, unlock the potential of AI in their projects.
Landing AI has made available (i) An SDK to support integrating applications with LandingLens’ computer vision capabilities, and (ii) A collection of application code samples that demonstrate building computer vision application deployments, that creators can adapt to their own applications. The SDK currently supports Python and JavaScript, with plans to add C#.
“Landing AI is dedicated to empowering businesses with cutting-edge technology, and that means providing developers, data scientists and other creators with the tools they need to take their computer vision projects to new heights,” says Andrew Ng, Landing AI CEO and noted AI pioneer. “With the release of our SDK and code sample repository, we aim to help users streamline the computer vision development process.”
Here’s what’s available from Landing AI’s SDK:
- Comprehensive Selection of AI Use Cases: Landing AI’s repositories cover a range of computer vision use cases, including object detection and Visual Prompting, a recently announced Landing AI capability that takes the framework of text prompting found in technologies such as ChatGPT and brings it to computer vision.
- High-Quality Code and Documentation: Each code sample is created by a team of AI experts so the code is functional and follows industry best practices.
- Ease of Integration and Customization: Computer vision projects often require customization and integration with existing systems. As such, the SDK is modular and easily adaptable so it can be seamlessly integrated into projects, saving time and development effort.
- Continuous Updates and Contributions: AI is a rapidly evolving field. The repository will be regularly updated with improvements and additional use cases. Landing AI encourages community contributions to foster collaboration and knowledge sharing among AI enthusiasts.
Landing AI is committed to fostering a vibrant community of developers, data scientists, and AI enthusiasts. LandingPad is a community of LandingLens users who share experiences, questions, and engage with others passionate about AI technology.
To learn how to use the code samples, take a look at Landing AI’s tutorial titled “Detect Suits in Poker Cards” explaining how to create an application that detects suits in playing cards. In this tutorial, anyone can use a webcam or smartphone camera to take images of playing cards. An object detection model developed in LandingLens will then run inference on the images. This code sample can be quickly adapted to new applications.
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