Showing 2 open source projects for "inventory management system visual studio code"

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  • Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK. Icon
    Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK.

    With Ditto Edge Server, you can join devices as small as a Raspberry Pi to a local mesh network and synchronize data across edge environments.

    Ditto's Edge SDK is the only thing your edge devices need to ensure your application is operational in any environment, regardless of network conditions.
    Learn More
  • Monitor production, track downtime and improve OEE. Icon
    Monitor production, track downtime and improve OEE.

    For manufacturing companies interested in OEE monitoring solutions

    Evocon is a visual and user-friendly OEE software that helps manufacturing companies improve productivity and remove waste as they become better.
    Learn More
  • 1
    ML workspace

    ML workspace

    All-in-one web-based IDE specialized for machine learning

    All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...
    Downloads: 0 This Week
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  • 2
    Image Quality Assessment

    Image Quality Assessment

    Convolutional Neural Networks to predict aesthetic quality of images

    ...The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as composition, clarity, and visual appeal. Instead of relying on simple image statistics, the system learns patterns that correlate with human judgments about image aesthetics and technical quality. The repository includes code for training models, performing inference, and evaluating predicted scores against labeled datasets. It also provides utilities for image preprocessing and data management that help prepare datasets for training deep learning models.
    Downloads: 0 This Week
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