Image Annotation Services · Computer Vision
Image Annotation Services
For computer vision and AI teams · 99.5% accuracy · 24-hour turnaround · from ₹2 per image
Expert-labeled bounding boxes, segmentation masks, polygons, keypoints, and 3D point clouds, delivered worldwide in COCO JSON, YOLO, Pascal VOC, or any custom format. Built by domain-trained annotators and verified through a multi-pass QC pipeline.
CAR 0.97
PERSON 0.94
TRUCK 0.99
BICYCLE 0.91
Image annotation services turn raw images into precisely labeled training data that computer vision models can learn from. Data Terminal provides end-to-end image annotation services for AI teams worldwide, from a single-class bounding box project to multi-million-image segmentation pipelines. Every label is produced by trained human annotators, verified through a multi-pass QC process, and delivered in the exact format your model expects.
Our teams work across autonomous driving, medical imaging, agriculture, retail, satellite, and security use cases, holding 99.5% accuracy at a fraction of US and European labeling costs. Whether you need a fast pilot or a dedicated annotation team scaled to 50,000-plus images per day, the workflow below is built to keep quality high and turnaround under 24 hours.
What We Annotate
Image Annotation Services: Every Type We Deliver
Bounding box, segmentation, polygon, keypoint, 3D point cloud, and OCR, each expert-annotated at 99.5% accuracy and delivered in your format.
Bounding Box
From ₹2/image
Tight and loose rectangular boxes for object detection. The most common annotation type for YOLO, Faster R-CNN, and SSD models.
Object DetectionSemantic Segmentation
From ₹8/image
Pixel-level class labeling for scene understanding. Every pixel assigned to a class, ideal for self-driving and satellite imagery.
Scene UnderstandingInstance Segmentation
From ₹10/image
Each individual object instance labeled separately. Enables counting, tracking, and part-level analysis at pixel accuracy.
Object TrackingPolygon Annotation
From ₹5/image
Precise polygonal outlines for irregular shapes. More accurate than bounding boxes for non-rectangular objects.
Precision ShapesKeypoint / Landmark
From ₹4/image
Dot-based skeletal annotation for pose estimation, facial landmarks, and body-joint detection models.
Pose EstimationPolyline & Lane
From ₹4/image
Line and polyline annotation for lane markings, road boundaries, and connected structures in ADAS datasets.
Lane Detection3D Point Cloud / LiDAR
From ₹15/object
Cuboid and segmentation labeling of LiDAR and 3D sensor data for autonomous driving and robotics perception.
3D PerceptionOCR & Text-in-Image
From ₹3/image
Text detection and transcription within images, receipts, and documents for OCR and document-AI pipelines.
Text ExtractionImage Classification
From ₹1/image
Whole-image class labels for recognition models. The fastest annotation type, with 99.5% inter-annotator agreement.
Image RecognitionQuality Methodology
Image Annotation Quality: How We Hit 99.5% Accuracy
99.5%
Average Accuracy Score
Accuracy is not a promise, it is a measured output. Every batch is scored against a gold-standard set before it ships, so the number you see is the number you get.
Step 01
Primary Annotation
Expert annotators assigned by vertical, whether AV, medical, retail, or satellite. Domain knowledge applied from image one.
Step 02
Peer Review
A second annotator reviews every label. Any box or mask below the accuracy threshold is flagged immediately for re-annotation.
Step 03
Gold Standard Validation
A 5% random sample is tested against pre-labeled gold images. The batch fails if any label drifts from baseline.
Step 04
Automated Accuracy Check
A script validates every completed batch. No annotation ships below the minimum threshold, ever.
99.5%
IoU / Pixel Accuracy
99.1%
Inter-Annotator Agreement
Zero
Missed Objects Post-QC
AI + Human
AI-Assisted Image Annotation, Human-Verified
Manual-only labeling is slow. Fully automatic labeling is inaccurate. We combine model-assisted pre-labeling with human verification, so you get the speed of automation and the accuracy of expert annotators, on the same dataset.
Foundation models like SAM handle the first pass. Trained annotators correct, resolve edge cases, and sign off every label. Hard cases are routed back through an active-learning loop, so accuracy climbs as the project scales, instead of drifting.
3–5x
Faster Than Manual
100%
Human-Verified Labels
Step 01
Model-Assisted Pre-Labeling
We pre-label with foundation models like SAM and your own trained models, so annotators refine instead of starting from a blank frame.
Step 02
Human Verification
Every AI-suggested label is checked and corrected by a trained annotator. Nothing ships on model confidence alone.
Step 03
Active Learning Loop
Low-confidence and hard cases are routed back for priority review, so the dataset improves round over round.
Step 04
Agreement Scoring
Inter-annotator agreement and IoU are tracked per batch to catch drift before it ever reaches your dataset.
Our Process
From Upload to Delivery in 24 Hours
01
Upload
Share images via secure portal, Google Drive, S3, or FTP. JPG, PNG, TIFF, DICOM, BMP, any format accepted. NDA signed first.
02
Annotate
Expert annotators work in CVAT, Labelbox, or your preferred tool, with model-assisted pre-labeling and domain specialists per vertical.
03
QC Review
Every image passes 3-layer quality control. Any label below threshold is re-annotated before delivery.
04
Deliver
Receive in COCO JSON, YOLO, Pascal VOC, or any custom format, with a full accuracy report included.
Industries Served
Image Annotation Services by Industry
Dedicated annotation teams per industry, trained on domain edge cases, not generalists.
Autonomous Vehicles
Pedestrian, vehicle, sign, and lane detection. Pixel-perfect segmentation plus tracking IDs at 50K+ frames per day.
Segmentation + TrackingMedical Imaging
Tumour localisation, cell detection, and surgical-instrument tracking. Precision-critical annotation by trained specialists.
Precision AnnotationAgriculture
Crop-disease detection, pest identification, and yield estimation from aerial imagery. Polygon and oriented-box specialists.
Aerial ImageryRetail & E-commerce
Product detection, shelf monitoring, and cashierless checkout. Multi-class annotation at catalogue scale.
Multi-classSatellite Imagery
Land-use classification, building detection, and road extraction from high-resolution geospatial data.
GeospatialSecurity & Surveillance
Person, vehicle, and object detection. Instance segmentation for crowd analytics and intrusion detection.
Real-time DetectionProof
Results From Real Annotation Projects
A snapshot of image annotation projects we have scaled to production. Client names withheld under NDA.
Autonomous Driving
ADAS perception dataset scaled to production
A European autonomous-driving team needed 2D bounding boxes plus semantic segmentation across millions of street-scene frames, with tight lane and pedestrian accuracy. We ran a calibration batch, locked the guidelines, then scaled a dedicated team.
2.4M
Frames labeled
99.6%
Mean IoU
50K/day
Peak throughput
Medical Imaging
Radiology segmentation for a diagnostic model
A clinical AI startup required pixel-precise organ and lesion segmentation on CT and MRI slices under strict data-handling rules. Domain-trained annotators worked inside a HIPAA-aware, access-controlled environment.
180K
Slices annotated
99.4%
Annotator agreement
HIPAA-aware
Workflow
Retail & E-commerce
Shelf-intelligence dataset at scale
A retail analytics platform replaced a slow in-house labeling process. We handled product detection and classification across store-shelf images with a fully managed team, cutting cost without losing accuracy.
1.2M
Shelf images
62%
Lower cost vs in-house
18 days
Pilot to scale
Security & Compliance
Your Images, Kept Secure
Data security is the first question serious AI teams ask. Here is how we answer it, before any image changes hands.
NDA by default
Every engagement is covered by a mutual NDA before a single image is shared, signed on your paper or ours.
Encrypted transfer & storage
Images and labels move over encrypted channels and sit on access-controlled infrastructure, never on personal devices.
Role-based access
Only assigned, vetted annotators touch your data. Access is logged and revoked the moment a project closes.
GDPR-aligned handling
Data-processing workflows follow GDPR principles, with data-residency options available on request.
HIPAA-aware medical pipelines
For healthcare data we run isolated, access-restricted pipelines with de-identification support built in.
Deletion on completion
Source data and working copies are permanently deleted at project close. On-premise and private-cloud (VPC) delivery available.
Formats & Tools
Works With Your Pipeline
Export Formats
COCO JSONYOLO TXTPascal VOC XMLCVAT XMLTFRecordCSVCustom
Annotation Tools
CVATLabelboxRoboflowSuperAnnotateV7 DarwinSegments.aiVGG (VIA)Custom API
If your pipeline requires a specific schema or tool integration, we build the connector at no extra cost.
Free Sample Offer
Try Before You Commit
Send us 50 images. We will annotate them free in 24 hours, your annotation type, your format, with an accuracy report. No payment. No commitment.
50 images annotatedAny annotation typeYour output formatAccuracy report included24h delivery
FAQ
Image Annotation Services: FAQ
Image annotation services turn raw images into precisely labeled training data for computer vision models. Providers label objects, regions, and attributes using techniques like bounding boxes, semantic segmentation, polygon annotation, and keypoint labeling. Data Terminal delivers image annotation services at 99.5% accuracy for AI teams worldwide, covering object detection, segmentation, pose estimation, and classification.
Data Terminal offers 2D bounding boxes (tight and loose), semantic segmentation, instance segmentation, panoptic segmentation, polygon annotation, keypoint and landmark annotation, polyline and lane annotation, 3D point cloud and LiDAR annotation, OCR and text-in-image labeling, and image classification. All annotation types are available with 99.5% accuracy and 24-hour turnaround.
Image annotation pricing ranges from ₹2 to ₹15 (roughly $0.03 to $0.20) per image depending on complexity. Simple bounding boxes start at ₹2 to ₹3 per image, polygon annotation is ₹5 to ₹10, and semantic segmentation is ₹8 to ₹15. Data Terminal offers volume discounts of 10 to 30% on projects above 1,000 images, and a free 50-image pilot so you can validate quality before you commit.
Semantic segmentation labels every pixel with a class, so all cars share one color. Instance segmentation identifies each individual object separately, so car 1, car 2, and car 3 are distinct. Instance segmentation is used for counting and tracking; semantic segmentation is used for scene understanding. Panoptic segmentation combines both. Data Terminal handles all three at scale.
Standard turnaround at Data Terminal is 24 to 48 hours for batches up to 10,000 images. Rush same-day delivery is available. For 100,000-plus image projects, parallel annotation teams deliver 50,000-plus images per day without dropping accuracy.
We deliver in COCO JSON, Pascal VOC XML, YOLO TXT, CVAT XML, TFRecord, CSV, and any custom schema your pipeline needs. Format conversion is included at no extra cost.
Data Terminal works in CVAT, Labelbox, Roboflow, SuperAnnotate, V7 Darwin, VGG Image Annotator, and custom in-house pipelines. We can annotate inside your existing platform or provide a fully managed environment, whichever keeps your review loop tighter.
Yes. Data Terminal serves AI teams across the US, Europe, the Middle East, and Asia, delivering remotely with time-zone-aligned communication. Our annotation studios are based in India, which lets us offer domain-trained annotators at 60 to 70% lower cost than US or European providers while holding 99.5% accuracy.
You do. All source images, labels, guidelines, and derived datasets are your property. We claim no rights over your data or the annotations we produce, and nothing is reused for any other client or purpose.
Every engagement starts with a mutual NDA. Data is transferred over encrypted channels and stored on access-controlled infrastructure, and only assigned, vetted annotators can view it. We follow GDPR-aligned handling, offer data-residency and on-premise options, and permanently delete source data on project completion unless you ask us to retain it.
Yes. We run a calibration batch to lock guidelines, then scale a dedicated team to your throughput. Projects routinely reach 50,000-plus images per day, and we keep trained annotators in reserve so volume spikes do not stall your model release.
Yes. We annotate directly in your platform when you have one, integrate with your storage (S3, GCS, Azure Blob), and build the export connector for your training pipeline at no extra cost. If you have no tooling, we provide a fully managed environment.
Guideline changes are expected on real projects. We version every guideline, re-run a small calibration batch on the new rules, and re-annotate affected images so your dataset stays internally consistent. Change requests do not reset your timeline or your accuracy.
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Get Your Images Annotated.
Free 50-image sample on your first project. Response in under 2 hours. Transparent pricing with no hidden costs.
Phone+91-9014387222
Emailcontact@dataterminal.co
WhatsAppReply in under 2 hours
LocationHITEC City, Hyderabad, India
