KopiKat
Label Studio
Gretel AI Beta²
Generated Photos Datasets
Computer Vision Annotation Tool (CVAT)
This Person Does Not Exist
AWS SageMaker Ground Truth
Face Generator
Universal Data Tool
Labelbox
CrowdFlower
Supervisely
Amazon Mechanical Turk
Labeling AI
Segments.ai
Playment
KopiKat generates a new, visually realistic duplicate of the original image, maintaining all critical data annotations. It alters the environment of the original images, for instance, adjusting factors like weather, seasons, and lighting conditions to add variety to datasets. This is crucial for fields such as object detection, neural network training, and transfer learning.
The Universal Data Tool (UDT) is an open-source web or downloadable tool for labeling data for usage in machine learning or data processing systems.
The Universal Data Tool supports Computer Vision, Natural Language Processing (including Named Entity Recognition and Audio Transcription) workflows.
The UDT uses an open-source data format (.udt.json / .udt.csv) that can be easily read by programs as a ground-truth dataset for machine learning algorithms.
KopiKat Universal Data ToolNo features have been listed yet.
KopiKat's answer
Our goal with Kopikat is to strengthen practical applications, especially in scenarios where collecting an extensive dataset proves to be difficult. Kopikat is ideally designed for datasets containing up to 5,000 images, a common feature of numerous real-world AI initiatives. It equips engineers with the ability to enhance mean average precision (mAP), broaden and vary datasets—a critical edge in fields like object detection, neural network training, and transfer learning.
KopiKat's answer
KopiKat's operation is remarkably simple and efficient for its users. All a user has to do is upload one image from their dataset. KopiKat then produces numerous images showcasing different scenarios, like alterations in illumination or weather, all the while preserving the annotations consistently. This attribute considerably expands the diversity of the dataset without requiring extra images, and creates a comprehensive, superior-quality model that introduces diversity beyond what traditional data augmentation techniques can offer. This method has demonstrated an improvement of over 5% in mean average precision (mAP), without any alterations to the AI model.
Label Studio - Open Source Data Labeling Platform for AI Model Tuning
Labelbox - Build computer vision products for the real world
Gretel AI Beta² - Generate unlimited synthetic data in minutes
CrowdFlower - Enterprise crowdsourcing for micro-tasks
Generated Photos Datasets - Reduce bias in AI systems with synthetic face datasets
Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...