Computer Vision Services & Solutions

Get premium support from world-class experts to implement computer vision the right way, by extracting real-time data from videos & images to accelerate your ML journey

Computer vision

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Amazon
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Cogknit

Making Sense of the Visual World to Train Computer Vision Applications

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.

The recent developments in Computer Vision technologies have overcome some of the limitations that humans face in accurately detecting and labeling objects from the vast amounts of data generated today from disparate systems. The computer effectively solves these 3 tasks:

  1. Automatically understand what the objects in the image are and where they are located.
  2. Categorize these objects and understand the relationships between them.
  3. Understand the context of the scene. 

Computer vision

  • Object Classification: What broad categories of objects are there?
  • Object Identification: Which type of a given object are there?
  • Object Verification: Which is the object in the photograph?
  • Object Detection: Where are the objects in the photograph?
  • Object Landmark Detection: What are the key points for the object in the photograph?
  • Object Segmentation: What pixels belong to the object in the image?
  • Object Recognition: What objects are in this photograph and where are they?
Data-collection-services

Data Collection Services

Training ML models to interpret & comprehend the visual world requires large volumes of accurately labeled image and video data. 

  • Source image/video data from over 60+ geographies
  • 2M+ images in multiple medical specialties like Radiology etc.
  • 60k+ Food & Document images covering 50+ variations with respect to the setting, illumination, indoor v/s outdoor, distance from the camera.

Data Annotation Services

From bounding boxes, semantic segmentation, polygons, polylines to keypoint annotation we can help you with any image/video annotation technique.

  • A fully managed, end-to-end data annotation services with software and workforce included, thereby simplifying the user experience.
  • An experienced workforce consisting of 30,000+ collaborators helps in labeling images & videos for CV use cases i.e., object detection, image segmentation, classification, etc.
Data-annotation-services
Managed workforce

Managed Workforce

We also offer a skilled resource that becomes an extension of your team to support you with your data annotation tasks, through tools that you prefer while maintaining the desired consistency and quality. Our skilled and experienced workforce apply the best practices learned by labeling millions of images & videos to deliver world-class data labeling for computer vision solutions.

AI Computer Vision Expertise

Image/Video Collection & Annotation Capabilities 

From image/video collection to annotation object recognition and tracking to semantic segmentation and 3-D point cloud annotations, we bring a greater understanding of the visual world with detailed, accurately labeled images and videos to improve the performance of your computer vision models.

Image collection

Image Collection

Video collection

Video Collection

Bounding box - image annotation

Bounding Boxes

Polygon annotation

Polygon Annotation

3d cuboids - image annotation

3D Cuboids

Image annotation semantic annotation

Semantic Segmentation

Image annotation landmark annotation

Landmark Annotation

Line segmentation - image annotation

Line Segmentation

Image transcription - cv

Image Transcription

Video transcription - cv

Video Transcription

Image classification

Image Classification

Image segmentation

Image Segmentation

Image keypoint annotation

Image Keypoint Annotation

Video classification

Video Classification

Video segmentation

Video Segmentation

Computer Vision 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

Car driver in focus image dataset

  • 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.

Landmark image dataset

  • Use Case: Landmark Detection
  • Format: Images
  • Volume: 80,000+
  • Annotation: No

Drone-based Video Dataset

84.5k drone videos of areas like College/School campus, Factory site, Playground, Street, Vegetable Market with GPS details.

Drone-based video dataset

  • Use Case: Pedestrian Tracking
  • Format: Videos
  • Volume: 84,500+
  • Annotation: Yes

Food Image Dataset

55k images in 50+ variations (w.r.t. food type, lighting, indoor vs outdoor, background, camera distance etc.) with annotated images

Food/ document image dataset with semantic segmentation

  • Use Case: Food Recognition
  • Format: Images
  • Volume: 55,000+
  • Annotation: Yes

Use Cases

Iot and healthcare ai

Healthcare AI

Train ML models to detect cancer moles in skin images or finding symptoms in MRI scans or patient's x-ray.

Facial recognition

Facial Recognition

Train ML models to identify images of people based on facial features & compare them with a database of facial profiles to detect & tag people.

Geospatial data & imagery analytics

Geospatial Applications

Annotation of satellite images & UAV photography to prepare datasets for geoprocessing, and annotate 3D point cloud for Geo.AI.

Ar/vr

Augmented Reality

With AR headset, place virtual objects in the real world. It can detect plane surfaces such as walls, tabletops, and floors - a very critical part in establishing depth & dimensions and placing virtual objects in the physical world.

Autonomous driving

Self-Driving Cars

Multiple cameras capture videos from a different angle to identify the boundaries of traffic signals, roads, cars, objects, and pedestrians nearby to train the self-driving cars to auto steer the vehicle and avoid hitting obstacles while driving the passenger safely.

Retail

Retail / e-Commerce

With computer vision in retail, the applications can offer personalized recommendations based on customers buying patterns & speed up business operations like shelf management, payments etc.

Why Shaip?

Competitive Pricing

As experts in training and managing teams, we ensure projects are delivered within the defined budget.

Cross-Industry Capability

The team analyzes data from multiple sources & is capable of producing AI-training data efficiently and in volumes across all industries.

Stay ahead of Competition

The wide gamut of image data provides AI with copious amounts of information needed to train faster.

Expert Workforce

Our pool of experts who are proficient in image/video annotation and labeling can procure accurate and effectively annotated datasets.

Focus on Growth

Our team helps you prepare image/video data for training AI engines, saving valuable time & resources.

Scalability

Our team of collaborators can accommodate additional volume while maintaining the quality of data output.

Our Capability

People

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

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

Platform

The patented platform offers benefits:

  • Web-based end-to-end platform
  • Impeccable Quality
  • Faster TAT
  • Seamless Delivery

Have a computer vision project in mind? Let’s connect

Computer Vision is a branch of AI that trains machines to interpret, analyze, and understand visual data, such as images and videos, similar to how humans see and process the world.

It works by using machine learning (ML) and deep learning models to classify, detect, and recognize objects in images/videos. Models are trained with annotated datasets to identify objects, landmarks, and patterns with precision.

Computer Vision is used in self-driving cars for obstacle detection, healthcare for analyzing medical images, retail for personalized recommendations, facial recognition, geospatial mapping, and augmented reality for placing virtual objects in the physical world.

Yes, Shaip customizes datasets based on your requirements, including specific geographies, demographics, objects, and annotation styles.

Annotation techniques include bounding boxes, polygons, semantic segmentation, 3D cuboids, keypoints, and line annotations, depending on the project’s requirements.

Shaip employs a team of 30,000+ skilled annotators and a 6 Sigma process to ensure accurate, high-quality datasets with rigorous quality checks.

Yes, Shaip’s services are designed to scale for projects of any size while maintaining consistency and quality.

All data is de-identified and complies with global standards such as GDPR and HIPAA, ensuring secure and ethical handling of sensitive information.

Pricing depends on factors like data type, volume, customization, and delivery timelines. Contact us for a personalized quote.

Shaip offers high-quality, customizable datasets, competitive pricing, expert annotators, and scalable solutions, making it a trusted partner for Computer Vision projects.

Delivery timelines depend on project size and complexity but are often designed to meet agreed deadlines without compromising quality.