Advancements in computer vision have drastically transformed how we interact with the world. Once just the stuff of science fiction, game-changing technologies like self-driving cars, virtual reality, and cashier-less stores are now commonplace, all thanks to computer vision. However, creating these technologies is far from simple. For artificial intelligence (AI) and machines to accurately “see” images and videos, they go through a particular process called image tagging.
Many industries heavily rely on quality image tagging—tons of it—to train machine learning applications to make the most accurate identifications predictions possible. This is a time-consuming and laborious process, so it is ideal to resort to proper image tagging services to ensure on-time completion and sustained success.
What are Image Tagging Services?
Image tagging services describe the process of identifying and labeling the contents of an image. This can be done manually by someone looking at the image and manually adding tags, or done automatically using machine learning technology. Due to the complexity of image data, image tagging involves a lot of techniques like object, facial, and scene recognition to make it easier for machine learning models to read and analyze image data.
Image tagging makes it easier to organize image data using predefined labels and categories, making them searchable for businesses and individuals.
Image tagging services have various applications. Here are some of its familiar use cases:
E-commerce: Shopping online wouldn’t be accessible if it weren’t for image tagging services. Online retailers tag their product images with relevant keywords such as color, size, and brand to make searchability easier and increase sales.
Social media: A trending hashtag is just one of the many uses of AI image tagging in social media. It improves your brand content’s searchability and reach.
Digital asset management: Tagging images with data like date, location, and creator helps to manage digital asset libraries and find specific assets easily.
Advertising: By analyzing and tagging ads with relevant keywords, topics, and demographics, marketers can optimize their advertising campaigns. This can help target the right audience and increase ad effectiveness.
Every AI project needs large amounts of manually tagged data to become successful. Without proper resources and staff, it will take a significant amount of time for a company to launch a project, which is why most businesses outsource to image tagging companies.
Benefits of Outsourcing Image Tagging Services
Outsourcing image tagging offers businesses, marketers, and individuals several advantages. Here are some of the key benefits of partnering with image tagging companies:
- Flexible Scalability: Project needs keep changing, and a vendor with a scalable workforce will be able to adapt to these changes to meet project needs swiftly. They can handle large volumes of images and can adjust resources according to the client's requirements.
- Value-driven Cost-effectiveness: Companies can save money by outsourcing their image tagging services to an existing vendor with trained staff and ready-to-use tools and technology. Outsourcing providers can offer flexible pricing models based on the volume of images and tagging complexity.
- Rapid Turn-around time: With their resources and hiring capabilities, image tagging companies adhere to delivery timelines, no matter the project’s scale.
- Outstanding Expertise and Technology: Image tagging companies have a trained workforce and the latest tools and technologies that ensure high accuracy and image tagging quality.
- Improved Efficiency: Outsourcing image tagging services can improve efficiency by streamlining tasks and freeing time and resources for core business activities.
How are Image Recognition Services Priced?
Each AI Image tagging project is unique, and some need complex requirements. Therefore, outsourcing companies look into various factors that impact image annotation pricing:
- Complexity - Pricing varies depending on the detailed and specialized tagging requests. An example is recognizing specific objects or faces, narrowing down to tagging their concrete details and features.
- Annotator Expertise - Trained and experienced workforce costs vary depending on the required subject matter experts.
- Data Volume - Prices vary depending on the number of images to be tagged within a timeline.
- Quality Assurance (QA) - Some companies require a secondary quality assurance (QA) team for additional review or building a customized QA workflow.
Given these factors affecting costs, image tagging companies offer various pricing models for their clients to consider:
- Pay-per-image: Some image annotation companies set a specific fee per image to be charged for a project depending on the number of tags required.
- Custom pricing: For a big project, vendors can offer a customized fee for businesses based on their prior relationship, the complexity of the project, etc.
- Subscription-based: Some businesses that have ongoing image annotation projects opt for a subscription-based model for a fixed quantity of image tags per month that can be scalable.
- Crowdsourcing: A business with only one-off needs can crowdsource to individuals who take freelance projects. A centralized platform like TaskVerse make it easy to distribute image tagging tasks to thousands of remote freelancers.
- Add-on service: Vendors usually offer image tagging as an add-on with other AI services like data collection, image hosting, etc.
Outsource Image Tagging Services with Us
Dubbed by the Everest Group as the World’s Fastest Business Process (Outsourcing) Service Provider in 2022 and highly rated in the Gartner Peer Insights Review, TaskUs offers a wide range of services to power computer vision, natural language processing, and content relevance. We specialize in providing quality data labeling and image tagging services for various tech industries.
One of our clients, a leading US-based autonomous vehicle company, partnered with Us to help enhance their AI training by scaling their image annotation needs.
The results:
Our partners can easily scale their data annotation program without sacrificing quality. By providing high-quality human talent combined with our people-first principles, we drive excellent results and exceed client expectations.
