Relevant Image Data Collection to bring AI to Life
Train Computer Vision applications, AI setups, Self-driving entities, & more to perfection with state-of-art Image Data Collection Services
Eliminate the bottlenecks in your image data pipeline now.
Featured Clients
Why Image Training Dataset is needed for Computer Vision?
Unique Artificial Intelligence systems and Machine Learning models need to be trained comprehensively for being considered unique. While audio and textual datasets are necessary to intelligently train NLP models, applications with Computer Vision as the core functionality must be fed with an image training dataset.
Smart ML models and setups that are tasked with identifying objects and patterns as part of their functioning need to be trained extensively. Starting from tracking interactions to human emotions, intelligent systems must have the basis to identify entities in the first place. The power of identification is provided by custom image data collection solutions.
Image data collection for computer vision systems comes with the following benefits:
- Unique image-specific repository
- Ability to label images as per requirements
- Access to truckloads of historical data
Professional Image Training Datasets
Any subject. Any scenario.
Applications that need facial and gestural tagging cannot be fed information, superficially. Instead, image data collection for machine learning models must be at par with the latest standards. At Shaip, we focus on providing access to comprehensive image training datasets with expert-level support towards scalability.
Professional image training datasets at Shaip focuses on all-inclusive solutions, including entity tracking, handwriting analysis, object identification, and pattern recognition. That’s not it! Image data collection services offered by Shaip also include:
- Remote and In-field data feeding
- Ability to scale solutions – continual dataset procurement
- High-quality and segmented data that is ready for mining
- Support for image-to-text transcription for OCR trained models
- Extensive support for human-specific analysis
- Secure data handling and management
Our Expertise
Image collection that precedes Subjects and Scenarios
At Shaip, we have an entire line-up of image data collection types, with algorithms synonymous with specific use cases. Add computer vision to your machine learning capabilities by collecting large volumes of image datasets (medical image dataset, invoice image dataset, facial dataset collection, or any custom data set) for a variety of use cases. At Shaip, we have an entire line-up of image data collection types, with algorithms synonymous with specific use cases. Various types of Image Datasets that we offer:
Document Dataset Collection
Intelligent applications dealing in credential authentication are best benefited by document datasets. Shaip offers the best possible image collection, involving usable training data relevant to invoices, receipts, menus, maps, identity cards, and more, for helping the system identify entities proactively
Facial Dataset Collection
Applications that need to be trained for gauging facial emotions and expressions are best served with our facial dataset collection. Apart from feeding a humongous volume of data, at Shaip we aim at cutting through the AI bias, by collating insights across a wide range of ethnicities and age groups.
Healthcare Data Collection
Improve the quality of your digital healthcare setup and accuracy of medical diagnostics with qualitative and quantitative healthcare datasets on offer. We provide medical images i.e., CT Scan, MRI, Ultra Sound, Xray from various medical specialties such as Radiology, Oncology, Pathology, etc.
Food Dataset Collection
If you ever plan on developing a smart app that can capture and identify food images, under different lighting conditions, our food dataset collection can be quite handy.
Automative Data Collection
Training the databases of self-driving cars with roadside elements, angle-specific insights, objects, sematic data, and more is possible with automotive datasets.
Hand Gesture Data Collection
If you have ever hand-swiped your mobile to sleep, you would be able to relate. Smart & IoT devices with sensors can benefit from our hand gesture data collection services.
Object image Collectioin
Our object image collection service provides a wide array of images featuring different objects in various contexts and lighting conditions.
Landmark Image Collection
We specialize in collecting images of landmarks from around the world. Our datasets cover multiple angles, times of day, and weather conditions
Handwritten Text Collection
Collection of handwritten text images in various languages & styles to develop AI models capable of recognizing and interpreting handwritten text with accuracy.
Image Datasets
Car Driver in focus Image Dataset
450k images of driver faces with car setup in different poses and variations covering 20,000 unique participants from 10+ ethnicities
- Use Case: In-car ADAS model
- Format: Images
- Volume: 455,000+
- Annotation: No
Landmark Image Dataset
80k+ images of landmarks from over 40 countries, collected based on custom requirement.
- Use Case: Landmark Detection
- Format: Images
- Volume: 80,000+
- Annotation: No
Facial Image Dataset
12k images with variations around head pose, ethnicity, gender, background, angle of capture, age etc. with 68 landmark points
- Use Case: Facial Recognition
- Format: Images
- Volume: 12,000+
- Annotation: Landmark Annotation
Food Image Dataset
55k images in 50+ variations (w.r.t. food type, lighting, indoor vs outdoor, background, camera distance etc.) with annotated images
- Use Case: Food Recognition
- Format: Images
- Volume: 55,000+
- Annotation: Yes
Reasons to choose Shaip as your Trustworthy AI Image Training Data Partner
People
Dedicated and trained teams:
- 30,000+ collaborators for Data Creation, Labeling & QA
- Credentialed Project Management Team
- Experienced Product Development Team
- Talent Pool Sourcing & Onboarding Team
Process
Highest process efficiency is assured with:
- Robust 6 Sigma Stage-Gate Process
- A dedicated team of 6 Sigma black belts – Key process owners & Quality compliance
- Continuous Improvement & Feedback Loop
Platform
The patented platform offers benefits:
- Web-based end-to-end platform
- Impeccable Quality
- Faster TAT
- Seamless Delivery
People
Dedicated and trained teams:
- 30,000+ collaborators for Data Creation, Labeling & QA
- Credentialed Project Management Team
- Experienced Product Development Team
- Talent Pool Sourcing & Onboarding Team
Process
Highest process efficiency is assured with:
- Robust 6 Sigma Stage-Gate Process
- A dedicated team of 6 Sigma black belts – Key process owners & Quality compliance
- Continuous Improvement & Feedback Loop
Platform
The patented platform offers benefits:
- Web-based end-to-end platform
- Impeccable Quality
- Faster TAT
- Seamless Delivery
Services Offered
Expert text data collection isn’t all-hands-on-deck for comprehensive AI setups. At Shaip, you can even consider the following services to make models way more widespread than usual:
Audio Data Collection Services
We make it easier for you to feed the models with voice data to help them explore the perks of Natural Language Processing in a more balanced way
Text Data Collection
Services
The true value of Shaip cognitive data collection services is that it gives organizations the key to unlock critical information found within unstructured data
Video Data Collection Services
Now focus on computer vision along with NLP for training your models to identify objects, individuals, deterrents, and other visual elements to perfection
Recommended Resources
Buyer’s Guide
Image Annotation & Labeling for Computer Vision
Computer vision is all about making sense of the visual world to train computer vision applications. Its success completely boils down to what we call image annotation – the fundamental process behind the technology that makes machines make intelligent decisions and this is exactly what we are about to discuss and explore.
Solutions
Computer Vision Services & Solutions
Computer vision is an area of Artificial Intelligence technologies that train machines to see, understand, and interpret the visual world, the way humans do. It helps in developing the machine learning models to accurately understand, identify, and classify objects in an image or a video – at a much larger scale & speed.
Blog
Image Annotation Types: Pros, Cons And Use Cases
The world is not been the same ever since computers started looking at objects and interpreting them. From entertaining elements that could be as simple as a Snapchat filter that produces a funny beard on your face to complex systems that autonomously detect the presence of minute tumors from scan reports, computer vision is playing a major role in the evolution of humankind.
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Frequently Asked Questions (FAQ)
Image data collection for AI/ML involves gathering visual data in the form of pictures or graphics. This data serves as input for training, testing, and validating artificial intelligence and machine learning models, especially those designed to process and understand visual information.
Image data collection begins by defining the specific requirements and objectives of a project. After which, images are sourced from databases, captured using cameras, or generated using computer graphics. Ensuring high-quality and diverse images is crucial. Once collected, these images are often labeled or annotated, providing context or classification to assist the machine learning model in its training phase.
Image data collection is fundamental for any machine learning project dealing with visual information. Quality and diverse image datasets allow for more accurate and robust model training, which in turn leads to better performance in real-world applications. This ensures that AI systems can recognize, interpret, and respond to visual cues effectively.
Several types of image data can be collected, depending on the project’s objective. This includes but is not limited to: photographs, satellite images, medical imagery like X-rays or MRIs, handwritten documents, scanned documents, facial photographs, thermal images, and even augmented reality (AR) and virtual reality (VR) captures. The type of image data sourced should align with the specific requirements of the AI/ML project in question.
