DigitSquare supports Rectangle, Polygon, Point, and Line annotation types.

Each industry has unique requirements and challenges that can be addressed through image/video processing. For example, in Agriculture, this technology can help monitor crop health and detect diseases. In the Retail sector, it can be used for inventory management and customer behavior analysis. Similarly, in the Automotive industry, image/video processing can assist in autonomous driving systems and driver monitoring. The possibilities are vast and diverse across different sectors. 

DigitSquare provides a 14-day free trial license for assessment, which can be upgraded to a licensed version after the trial period ends. 

You can access it using the Web Browser. 

No, DigitSquare also supports Polygon annotation.

DigitSquare provides various pricing tiers that depend on volume and the quantity of annotations needed. For more details, please get in touch with our Sales team. 

No coding is required; this tool is tailored for ML Engineers and designed to be accessible to them.

DigitSquare adheres to GDPR regulations.

DigitSquare ensures data security through encryption and the implementation of extensive security measures. 

There are two options: 

Option 1 – Using annotated data sets, generate training models. 

Option 2 – Using unannotated data sets, auto label to annotate and generate models. 

Models generated using globally available standard formats. (Pytorch, TensorFlow, ONNX etc.). 

• Synthetic Image generation is the creation of artificially generated images that look as realistic as real images.  

• ML Engineers often require highly quantitative accuracy, and diverse datasets to train and build accurate ML models.  

• Synthetic data helps in reducing the costs of data collection and data labelling.  

• In addition to lowering costs, synthetic raw data helps address privacy issues associated with sensitive real-world data. 

• Types of Synthetic Data: 

• • Text data: Synthetic data can be artificially generated text in natural language processing (NLP) applications. 

• • Tabular data: Tabular synthetic data refers to artificially generated data like real-life data logs or tables useful for classification or regression tasks. 

• • Media: Synthetic data can also be synthetic video, image, or sound used in computer vision applications. 

Precision Image and Video Annotation 

DigitSquare AI image annotation platform is highly flexible, allowing users to customize it for diverse projects by defining their own annotation categories, labels, and attributes. 

Specialized Data Labeling 

DigitSquare provides Rectangle, Polygon, Point, and Line labeling services with advanced technology, ensuring accurate and efficient labeling of large datasets for high-quality results. 

Auto-Labelling Datasets 

DigitSquare provides annotated data for training models and utilizes unannotated data for auto-labeling, speeding up ML model training with automatic labeling in seconds. 

Enhancing Efficiency with 90% Auto-Labelling 

DigitSquare has a 90% auto-labelling rate, requiring only 10% manual intervention. This boosts efficiency, streamlining data processing, and minimizing errors for maximum productivity. 

Collaborative Workflow Management 

DigitSquare ensures team collaboration and streamlined workflow management for annotating large datasets. Multiple team members can work simultaneously on various tasks, enhancing project completion speed. 

Customizable Data Annotation 

DigitSquare AI image annotation platform is highly flexible and can be customized to meet specific needs of different projects. It allows users to define their own annotation categories, labels, and attributes, making it suitable for a wide range of data annotation tasks.  

Cost-Efficient Data Labeling 

DigitSquare dataset management tool provides cost savings in the process of labeling and categorizing large volumes of data. This fast and accurate image annotation automates the task, allowing faster turnaround times, enabling businesses to quickly analyze and extract valuable insights from their datasets.   

Scaling ML Models with Effective Data Annotation 

It scales machine learning models for larger datasets and complex tasks. It labels data, aiding in pattern recognition and accurate predictions, enabling models to generalize and label unseen data. 

Ensures Data Security and Privacy 

Your data is secure in an encrypted manner to protect you. We continuously monitor and update our security protocols to ensure the highest level of data protection. Additionally, we employ industry-standard encryption algorithms to safeguard your information from unauthorized access.