Label large size of image datasets with automated workflow. Get high quality training data for computer vision use case.
Draw bounding boxes on objects in any image and class
Classify images and complete dataset with ease
Assign multiple labels to a single image.
Automatic draw segment on object in image with precision.
Draw bounding boxes on objects in any image and class
Draw bounding boxes on objects in any image and class
Draw bounding boxes on objects in any image and class
Draw bounding boxes on objects in any image and class
Faster annotation to images with cutting edge auto labeling and programatic labeling features
Leverage open source or own pre-trained models to label images faster
Start with manual ground truth creation and soon our active learning will kicks in trained on perfectly annotated data.
Accelerate auto labeling with large foundation models like CLIP, SAM, DINO and many more
Build custom automated data workflows, collaborate in real-time, QA review, with complete visibility into your DataOps
Create and automate image labeling workflows to streamline the annotation projects. Add multiple users with multiple roles, multiple review cycle, build consensus with inter-annotator agreement, and annotation stages. Make your project managable.
Get professional annotators and domain experts who care about quality and accuracy. We provide fully managed service, so that you can focus on other important aspects.
Manage image annotation ptoject with comprehensive dashboard to track progress and quality.
Track time spent per file, annotation completed and accuracy in real time for rach annotator
Add consensus between annotator to automatically improve the accuracy, model assisted QA and more
Create a batch run on your data import/export with cloud and save time
Image annotation tool provide you capability to easily manage image labeling project by bringing human-in-the-loop and design custom workflow to ensure quality annotation on images. It gives the fexibility to chose from different type of annotation tasks like drawing bounding boxes, segmentation, polygon or polyline. Labellerr also provide high level of automation to complete the process 99X faster.
Image annotation is prerequisite to prepare your visual data for model training. It helps algorithm to identify the objects in the images or classify them based on the criteria.
Image annotation is very manual and time consuming task which requires multiple steps to ensure the quality. Managing the workforce, quality and speed become huge challenge for AI teams of all sizes. Labellerr helps to tackle these challenges with its Gen-AI based annotation tool.
Medical imaging comes mainly two format -2D and 3D image. Classification, detection and segmentation are the most common type of annotation that requires to build AI model for medical use cases.
An image annotation platform should support collaboration, model assisted labeling and QC workflow to ensure faster and accurate image labeling.
Labellerr uses best practices of data protection and privacy by implementing pseudonymization, redaction and masking based on PII. Enhanced authentication, IAM (Identity and access management) provided by third party cloud providers ensures data security and privacy.
We support all kind of image format.
By writing us at support@tensormatics.com to get instant remedy to queries (edited)