GGHL

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GGHL is an open-source implementation of a General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection. It provides a framework for researchers and engineers to experiment with advanced object detection techniques.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is GGHL?

GGHL is an open-source implementation of "A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection." This project, hosted on GitHub, provides the code and resources for researchers and engineers to explore and apply advanced object detection methods, particularly for arbitrarily-oriented objects. It includes functionalities for training, distributed training, and testing, along with support for the DOTA dataset. The implementation features a polygen NMS using shapely and numpy for compatibility across systems, with an option for a faster C++ version. GGHL also offers pre-trained weights for various datasets and integrates with popular deep learning frameworks, making it a valuable resource for those working on computer vision tasks.

Best used for

Ideal for developers and data scientists who need to implement advanced object detection models, experiment with novel label assignment techniques, and train models on complex datasets like DOTA. Especially valuable for research in computer vision and developing solutions for arbitrarily-oriented object detection.

Common actions

implement object detection

train AI models

research computer vision

label image data

automated workflowopen-sourcedeepfakelow-code/no-codecollaborationgithub copilotface swapping"AI Agents"workflows

Capabilities

Key features

Gaussian heatmap label assignment
Arbitrary-oriented object detection
DOTA dataset support
Polygen NMS implementation
Distributed training
Pre-trained model weights

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the primary purpose of GGHL?

GGHL is an implementation of a General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection. Its main purpose is to provide a framework for researchers and engineers to develop and test advanced object detection models, particularly for objects with arbitrary orientations.

What datasets does GGHL support?

GGHL primarily supports the DOTA dataset, which is common for arbitrary-oriented object detection tasks. It includes tools and scripts to convert DOTA dataset formats into the specific format required for training within the GGHL framework.

Does GGHL offer pre-trained models?

Yes, GGHL provides pre-trained models for various datasets, including DOTA, SKU, and DOTAv1.5/v2.0. These weights are available for download via Google Drive or Baidu Disk, allowing users to quickly get started with testing or fine-tuning.

What are the system requirements for GGHL?

GGHL requires Linux (Ubuntu 18.04, GCC>=5.4) or Windows (Win10) operating systems. It also needs CUDA > 11.1, Cudnn > 8.0.4, and PyTorch (version 1.11 is recommended for distributed training) along with other dependencies listed in its requirements.txt file.

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