Handle data 10X faster , reach outcomes with Visual AI in weeks instead of months
Upload media data into highly scalable data lake storage. Automated metadata management And effective centralized storage management.
Extract files from a ZIP archive, Some files are simply too important to even think about losing, So keeping a copy of the folder is better than losing information, Moving files between folders.
Share files with your team to access the same set of files you'd like to use.
We tend to lose sight of where files are being used. Track each file using lineage feature.
Single label classification allows you to label images containing exactly one of multiple classes.
Multi label classification allows you to classify datasets with more than one target variable. The given input prediction may belong to more than one label. Several labels that are the outputs for a given prediction.
2D Object detection is a computer vision technique for locating instances of objects in images.
3D object detection involves recognizing and determining 3D information, such as pose, volume, or shape, of user-chosen 3D objects in a photograph or range scan.
Semantic segmentation is the process of associating each pixel of an image with a class label. Multiple objects of the same class as a single entity.
Human Pose Estimation (HPE) is a way of identifying and classifying the joints in the human body. Essentially it is a way to capture a set of coordinates for each joint (arm, head, torso, etc.,) which is known as a key point that can describe a pose of a person. The connection between these points is known as a pair.
Quickly annotate images with AI-based segmentation tools that also reduce the number of clicks per annotation.
Image editing refers to modifying or improving digital or traditional photographic images using different techniques, tools or software. Images produced by scanners, digital cameras or other image-capturing devices may be good, but not perfect.
Share the dataset with your team to access the same set of images where users can annotate the same dataset.
The image augmentation carried out in the Swell application, is stored as a separate dataset version.
Video annotation is the process of labeling or tagging video clips which are used for training computer vision models to detect or identify objects. Unlike image annotation, video annotation involves annotating objects on a frame-by-frame basis to make them recognizable for machine learning models.
Synthetic data is information that's artificially manufactured rather than generated by real-world events. Synthetic data is created algorithmically, and it is used as a stand-in for test datasets of production or operational data, to validate mathematical models and, increasingly, to train machine learning models.
Cut frames from the video. You can either extract all the pictures or a specific time range can be cut. Finally , you can save the images you think it's important.
Train datasets with cutting-edge models. In addition, you can quickly Customize Model Parameters, Compare and analyze multiple training outcomes in one place.
Test the trained model, with our inference flow and see what works best for you.
A dashboard for time-generated tickets for better incident monitoring.
Schedule the deployment of trained models in less than a minute, resulting in a real-time ticket and alert generation.
Why Kandula AI?
Kandula AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance.
Work upon Single Label Classification, Multi Label Classification, 2D Annotation, 3D Annotation, Object Detection , Semantic Segmentation , Instance Segmentation , Landmark.
Annotate with BBOX to Segmentation , Extreme Points and Interactive Segmentation.Draw Regions with BBOX , Pen Tool, Polygons, Adjust Image Brightness , Sharpness , Contrast , Hue.
Choose images from Videos in real time. Augment images by generating Synthetic images over 40+ Scenarios. Stitch Images into Panoramas. Crawl Images from Internet, based on the annotated regions.
See the how No code AI And Data management can scale Visual AI adoption by 10X.