Computer Vision is the applied deep learning discipline that enables computer systems to extract high-fidelity semantic information, detect patterns, and segment objects from digital images and video sequences. hjLabs.in delivers custom visual quality control, industrial defect detection, and OCR ingestion systems for production teams across the United States, United Kingdom, and the Gulf region, typically reaching 96% to 99% recall on critical inspection lines within 4 to 8 weeks. Deployed edge and cloud systems start at USD 12,000.
Free 30-minute scoping call — we tell you up-front whether CV is the right tool for your problem.
Working systems you can open right now, without talking to us. There are no client logos below and no testimonials — we will not publish proof we cannot substantiate. What we can put in front of you is software hjLabs.in built, deployed and keeps running in public. Open it, push on it, and judge the engineering yourself before you spend time on a call.
Open any of these pages and the model downloads into your browser and runs on your own GPU through WebGPU — nothing is uploaded to a server. The catalogue behind them holds 139 open models across 22 task types, including OCR. It is the fastest way to see what current open vision models do and do not handle on your kind of image.
We transcribed DICOM PS3.15 Annex E Table E.1-1 — the Basic Application Level Confidentiality Profile — in full: 652 attributes, each carrying the standard’s own action code and VR. De-identification overwrites element values in place at their existing byte offsets, so the rest of the file, pixel data included, stays byte-identical to the original. It runs entirely in your browser; the study is never uploaded.
hjLabs.in is a machine builder as well as an AI shop. The CNC router, selective soldering robot, wire cutter, spring coiler and IoT transformer winder below are our own products, on this same website, with real prices on them. The people writing the models also own the mechanics, the electronics and the firmware — very few AI consultancies can say that.
We are a small specialist team, not a large consultancy, and we are not going to dress up as one. Here is what that actually buys you.
There is no account-manager layer between you and the person writing the code. The engineer who takes your scoping call is the engineer on your project, and stays reachable for the length of it.
hjLabs.in designs, manufactures and sells production machines — CNC routing, selective soldering, wire cutting, spring coiling, transformer winding. When a vision model has to survive a real factory line, cameras, lighting, PLCs and vibration are our day job, not a subcontractor’s.
Live tools you can open, open-source repositories you can read, and a standards implementation you can check line by line against the DICOM specification. You do not have to take a claim on trust when you can go and test it.
Four use-case patterns we ship over and over — each with measurable ROI.
Real-time inspection of PCBs, weld seams, injection-moulded parts, textile rolls and packaged goods. We typically reach 96 to 99 percent recall on critical defects with a 1 to 3 percent false-positive rate. Models run on Jetson Orin at 30 to 120 FPS per camera. CV inspection pairs especially well with our in-house automated PCB soldering line — defective joints flagged at the camera close the loop back into the solder profile within seconds.
Invoice extraction, KYC document parsing, handwritten form digitisation, label and serial-number reading on the production line. Combines TrOCR, PaddleOCR and Donut-style document transformers with rule-based post-processing to hit 99+ percent field-level accuracy.
Person/vehicle detection, intrusion zones, PPE compliance (hard-hat, vest, glove detection), licence-plate recognition, queue-length and dwell-time analytics. Edge-only options available for sites where footage cannot leave the premises.
Crop-health analysis from multispectral drone imagery, weed/pest detection, fruit counting and yield estimation, tree-canopy mapping. We process orthomosaics in QGIS / OpenDroneMap pipelines and serve the predictions back as GeoJSON for farm-management software.
The same tools we use in production, picked per workload — never “one stack fits all”.
YOLOv8, YOLOv10, RT-DETR, Detectron2, SAM 2, Mask R-CNN
OpenCV, Roboflow, CVAT, Albumentations, Supervision
NVIDIA Jetson Orin, Coral TPU, ONNX Runtime, TensorRT, OpenVINO
Vertex AI Vision, AWS Panorama, Azure Custom Vision, Roboflow Hosted
A six-step path from first call to a model that earns its keep in production.
We look at sample images/videos, ambient lighting, camera angles and the existing label set. Output: a one-page feasibility note that says go, no-go, or fix-the-optics-first. If your existing dataset is low-resolution or noisy, try our free AI upscaler and denoiser on a handful of frames before the review — it often makes the optics call obvious.
Pick label schema (bbox vs polygon vs mask), set inter-annotator agreement targets, and bootstrap with SAM 2 auto-segmentation on Roboflow to cut manual labeling 60 to 80 percent.
Benchmark three to five candidate architectures on your eval set. We optimise for the metric you actually care about (recall on critical defects, mAP at IoU 0.5, or character-error rate for OCR), not academic leaderboards.
Latency, bandwidth, privacy, fleet size and total cost of ownership all go on a spreadsheet. We pick Jetson, Coral, on-prem GPU, or cloud — and tell you exactly why.
A held-out test set built from production conditions, plus a stress set of edge cases. Confusion matrix, per-class precision/recall, and a side-by-side video diff on real footage before sign-off.
CI/CD for models, drift dashboard (Evidently or Arize), one-click retrain, and an on-call SLA for the first 90 days. Customers retrain via alerts, not via panic.
Engagement-based, not per-token. Senior CV engineers, transparent scope.
Single use case PoC, 3-4 weeks
Real-time deployment, 8-12 weeks
Multi-camera, multi-site, 16-24 weeks
Six questions every engineering leader asks before greenlighting a CV project.
Explore the rest of the hjLabs.in AI/ML and automation portfolio.
Bring sample footage. We’ll tell you what data, optics and model class will actually work — and what will not.
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