Colabeler Description
Image categorization, bounding box detection, polygon annotation, curve tracing, and 3D positioning. Additionally, video tracking, text categorization, and named entity recognition are supported. Custom task plugins allow users to develop their own labeling tools. Files can be exported in PascalVoc XML format, identical to that used by ImageNet, as well as in CoreNLP format. The platform is compatible with Windows, Mac, CentOS, and Ubuntu operating systems. This versatility ensures that users can seamlessly integrate it into their existing workflows.
Colabeler Alternatives
Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
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Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Google Cloud Vision AI
Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.
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TrainingData.io
Harnessing artificial intelligence to enhance the development of more effective AI solutions involves several key components. These include tools for pixel-perfect annotation, systems for managing annotator performance, builders for creating labeling instructions, and robust controls for data security and privacy. By integrating these elements, organizations can ensure a more precise and efficient training process for their AI models. Additionally, the implementation of such technologies can lead to improved outcomes and greater trust in AI applications.
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Integrations
API:
Yes, Colabeler has an API
No Integrations at this time
Company Details
Company:
Colabeler
Headquarters:
China
Website:
www.colabeler.com
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Product Details
Platforms
Windows
Mac
Linux
Types of Training
Training Docs
Customer Support
Online Support
Colabeler Features and Options
Data Labeling Software
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
Colabeler Lists
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