Showing 3 open source projects for "object recognition"

View related business solutions
  • Stop vibe-debugging. Icon
    Stop vibe-debugging.

    Plug Claude into your app's actual errors.

    AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
    Free 30 days.
  • Your monitoring isn't a stack. It's a pile. Fix that. Icon
    Your monitoring isn't a stack. It's a pile. Fix that.

    Errors, performance, logs, uptime. One install, one invoice, one UI.

    Replace Datadog, New Relic, and Sentry without adding three more dashboards.
    Free 30 days.
  • 1
    Qwen3-VL

    Qwen3-VL

    Qwen3-VL, the multimodal large language model series by Alibaba Cloud

    ...Qwen3-VL is built for complex tasks such as GUI automation, multimodal coding (converting images or videos into HTML, CSS, JS, or Draw.io diagrams), long-context reasoning with support up to 1M tokens, and comprehensive video understanding. It also brings advanced perception capabilities, including spatial grounding, object recognition, OCR across 32 languages, and robust handling of challenging inputs like low-light or distorted text.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    MediaPipe Face Detection

    MediaPipe Face Detection

    Detect faces in an image

    The MediaPipe Face Detection model is a high-performance, real-time face detection solution that uses machine learning to identify faces in images and video streams. It is optimized for mobile and embedded platforms, offering fast and accurate face detection while maintaining a small memory footprint. This model supports multiple face detections and is highly efficient, making it suitable for a variety of applications such as augmented reality, user authentication, and facial expression analysis.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 3
    Blazeface

    Blazeface

    Blazeface is a lightweight model that detects faces in images

    Blazeface is a lightweight, high-performance face detection model designed for mobile and embedded devices, developed by TensorFlow. It is optimized for real-time face detection tasks and runs efficiently on mobile CPUs, ensuring minimal latency and power consumption. Blazeface is based on a fast architecture and uses deep learning techniques to detect faces with high accuracy, even in challenging conditions. It supports multiple face detection in varying lighting and poses, and is designed...
    Downloads: 3 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo