Data labeling process for image annotation is not only critical but time taking. It creates training data sets for machine learning and AI model development. And the cost of such training data also depends on cost labeled data available for such needs.
Actually the cost of entire machine learning project is also pricing of correlated with the pricing of annotated data. The images labeled by the annotators using their efforts and skills also needs exploitation of various other resources to produce the data.
How Pricing of Data Labeling and Annotations Determined?
And the pricing for data labeling and annotations is decided while considering the various factors like complexity and volume of the data sets. The cost of entire data annotation project is determined by types of annotation like text, images or videos and what types of annotation technique is required to annotate the data.
While annotating an image with bounding box annotation, the time and efforts are far less than semantic segmentation that requires more experience with extra precautions to annotate the outline the object of interest in an image to make it recognizable to machines through computer vision for machine learning training.
Depending on The Complexity and Volume of Data
Similarly, there are many techniques to annotate or label the data. The rate for per image labeling is fixed, and cost of entire data labeling project is decided as per the total number of quantity required to train a ML algorithm.
However, with high volume of data requirement, the rates can be negotiated as per the bargaining power of buyer and supplier. However, more or less, the pricing of data labeling and annotations do not get affected due to lump sum payment.
Cogito is one of the leading image annotation companies, providing the data labeling service to annotate the different types of images with best level of accuracy. The Image Annotation Pricing of Cogito is far lower than other competitors, and Cogito has worked for well-known clients working on AI and ML projects to make supply them high-quality data sets to make their project successful and functional in real-life use.
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