awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
Call-for-Code avatar

Call-for-Code/DroneAid

0
View on GitHub↗
141 stars·58 forks·HTML·Apache-2.0·8 views

DroneAid

DroneAid uses machine learning to detect calls for help on the ground placed by those in need. At the heart of DroneAid is a Symbol Language that is used to train a visual recognition model. That model analyzes video from a drone to detect and count specific images. A dashboard can be used to…

Features

  • Computer Vision - Machine learning for finding persons in disaster zones.

Star history

Star history chart for call-for-code/droneaidStar history chart for call-for-code/droneaid

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to DroneAid

Similar open-source projects, ranked by how many features they share with DroneAid.
  • achaiah/pywickachaiah avatar

    achaiah/pywick

    400View on GitHub↗

    High-level batteries-included neural network training library for Pytorch

    Python
    View on GitHub↗400
  • ailab-cvc/yolo-worldAILab-CVC avatar

    AILab-CVC/YOLO-World

    6,425View on GitHub↗

    YOLO-World is a vision-language framework and open-vocabulary object detection model. It identifies objects in images and video based on free-form text prompts without requiring predefined category labels. The system enables the identification of arbitrary objects by fusing image features with text embeddings. It includes a specialized tool for automated image labeling, which generates bounding box annotations for custom datasets using text-based prompts. The project provides a deployment pipeline for converting models into quantized ONNX and TFLite formats, supporting real-time inference on

    Python
    View on GitHub↗6,425
  • airctic/icevisionA

    airctic/icevision

    0View on GitHub↗
    View on GitHub↗0
  • 1adrianb/face-alignment1adrianb avatar

    1adrianb/face-alignment

    7,518View on GitHub↗

    This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets. The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction. The toolkit includes capabilities for batch image p

    Python
    View on GitHub↗7,518
See all 30 alternatives to DroneAid→

Frequently asked questions

What does call-for-code/droneaid do?

DroneAid uses machine learning to detect calls for help on the ground placed by those in need. At the heart of DroneAid is a Symbol Language that is used to train a visual recognition model. That model analyzes video from a drone to detect and count specific images. A dashboard can be used to…

What are the main features of call-for-code/droneaid?

The main features of call-for-code/droneaid are: Computer Vision.

What are some open-source alternatives to call-for-code/droneaid?

Open-source alternatives to call-for-code/droneaid include: achaiah/pywick — High-level batteries-included neural network training library for Pytorch. ailab-cvc/yolo-world — YOLO-World is a vision-language framework and open-vocabulary object detection model. It identifies objects in images… airctic/icevision. alankbi/detecto — Build fully-functioning computer vision models with PyTorch. albu/albumentations — Albumentations is an image augmentation library and computer vision preprocessing tool designed to expand datasets for… 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a…