Showing 2 open source projects for "python samples"

View related business solutions
  • MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers. Icon
    MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers.

    Trusted by Operational Leaders Across the Globe

    Your day-to-day maintenance tasks, simplified. MaintainX eliminates the paperwork, so you can spend less time on your clipboard and more time getting things done.
    Learn More
  • Supercharge Your Manufacturing with Easy MRP and MES Software Icon
    Supercharge Your Manufacturing with Easy MRP and MES Software

    Designed for SME manufacturers who want to reduce wasteful manual processing, save time and increase profits.

    Flowlens eliminates stock-outs, shortage and overstocks, avoiding costly production delays. Stay in control of inventory levels and keep production running smoothly with real-time visibility and easy-to-use stock management. Import bulk data with ease.
    Learn More
  • 1
    Hello AI World

    Hello AI World

    Guide to deploying deep-learning inference networks

    ...The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. Follow these directions to integrate deep learning into your platform of choice and quickly develop a proof-of-concept design.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    Objectron

    Objectron

    A dataset of short, object-centric video clips

    The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB