Labelling training data acts as the first step in the machine learning development cycle under Computer Vision. Consider we need to train a machine learning model to identify a specified category of objects from the collection of data. We would need to collect representation data samples which have to be classified and analysed along with a Machine Learning algorithm for handling each sample.
As an initial step after receiving these resources along with service confirmation, our ML engineers shall start annotating items in the dataset according to the instructions provided. On completion of labeling, the dataset can be exported and used in further machine learning development. Our labeling services shall replace the manual annotation process with automation via a user-friendly interface that eases the annotation and parameter defining process.
The solution allows you to categorise any dataset (image/videos) along with tagging to customisable classification.
Make faster and accurate image segmentation to support specific use case including instances, custom attributes, etc.
Automate identification process using tools such as box, polygon, point and line to construct a predictable pattern of high-quality training data which trains ML powered computer vision system on finding or identifying objects in image and video data.
5 step process: How it works?
We have a team of skilled Data Processing Executives (DPE) who are expertise in handling and processing data along with segmenting and labeling.