Image Generation
& Computer Vision

AI-powered visual intelligence — from generating photorealistic images to detecting defects at 120fps. We build both sides of the visual AI spectrum.

Two disciplines.
One visual intelligence.

Visual AI divides into two fundamentally different problems: making machines understand what they see, and making machines create what you imagine. Most companies focus on one. YIME does both.

Computer vision for analysis, automation, and inspection. Image generation for creative production, synthetic data, and brand assets. Deployed on cloud, edge, or embedded — wherever your use case lives.

YOLOv9 Stable Diffusion SAM 2 DALL·E OpenCV TensorRT PyTorch ONNX
Computer Vision

Two sides of
visual AI

Select a discipline to explore what YIME builds in each domain — from detection pipelines to generative models.

Object Detection & Tracking

Real-time detection and multi-object tracking using YOLOv9, DETR, and ByteTrack — from single-frame classification to temporal trajectory analysis across video streams.

Semantic & Instance Segmentation

Pixel-level understanding of scenes using SAM 2, Mask R-CNN, and custom segmentation heads — for medical imaging, autonomous systems, and industrial inspection.

Visual Quality Inspection

Automated defect detection on production lines — surface anomalies, dimensional tolerance violations, contamination — at line speed with edge deployment.

Video Intelligence & Action Recognition

Behavior detection, crowd analytics, pose estimation, and activity recognition from CCTV, drone, or body-cam footage in real time.

Face & Biometric Recognition

Identity verification, liveness detection, and face attribute analysis — built with privacy safeguards and compliant with GDPR-aligned data handling.

Medical Image Analysis

AI-assisted radiology, pathology slide analysis, and diagnostic support — trained on domain-specific datasets with explainability (Grad-CAM) built in for clinical trust.

OCR & Document Intelligence

Structured data extraction from invoices, forms, IDs, and handwritten documents — including layout understanding and table parsing at scale.

3D Vision & Depth Estimation

Monocular depth estimation, point cloud processing, and 3D scene reconstruction for robotics, AR, and spatial computing applications.

Fine-tuned Diffusion Models

Custom Stable Diffusion / SDXL models fine-tuned on your brand assets, product catalog, or visual style — generating on-brand images without a photoshoot.

Product & Commercial Image Generation

Automated product photography, lifestyle imagery, and ad creative generation — swap backgrounds, generate variants, and produce thousands of images in minutes.

Synthetic Data Generation

Generate labeled training data for CV models where real data is scarce, expensive, or sensitive — synthetically augmenting datasets for medical, industrial, and autonomous applications.

Image Editing & Inpainting

Intelligent background removal, object insertion, style transfer, and context-aware inpainting — automated post-production workflows at scale.

ControlNet & Guided Generation

Pose-guided, edge-guided, and depth-guided image generation using ControlNet for precise structural control over generated output.

Avatar & Virtual Character Generation

Consistent digital humans and characters for games, VR, and media — built with identity preservation across multiple scenes and lighting conditions.

Architectural & Design Visualization

AI-generated architectural renders, interior design concepts, and spatial mockups from sketches or blueprints — reducing visualization turnaround from weeks to hours.

Multi-modal Image-Text Models

CLIP-based retrieval, image captioning, VQA, and visual grounding — connecting images to language for search, accessibility, and content intelligence.

Every pixel processed.
Every object understood.

Our object detection models return structured predictions: class labels, bounding boxes, confidence scores, and segmentation masks — all in real time.

  • 98.5%+ detection accuracy on custom-trained datasets
  • Multi-class detection across 100+ simultaneous objects
  • Sub-50ms inference on edge hardware
  • Confidence calibration for production safety
Live Detection Output — YOLOv9 — 47ms / frame
Vision Demo
Person 0.97
Vehicle 0.94
Bag 0.89
Ground 0.91
Person
97%
Vehicle
94%
Bag
89%
Ground
91%

Speed matters when
video doesn't pause

Real-time CV applications demand deterministic low-latency inference. We optimize models end-to-end — from architecture selection and quantization to TensorRT compilation and edge deployment.

Inference latency by deployment target
YOLOv9 object detection, 1080p input, batch size 1
Cloud GPU
22ms
NVIDIA T4
35ms
Jetson Orin
47ms
Jetson Nano
88ms

Where visual AI
creates real value

Manufacturing QC

Automated visual inspection replacing manual checking — 98.5% defect detection accuracy at line speed with zero fatigue.

Medical Diagnostics

Radiology AI, pathology slide analysis, and surgical instrument tracking — with Grad-CAM explainability for clinical trust.

Retail Visual Search

AI-powered product search by image, automated catalog tagging, and planogram compliance monitoring from shelf photos.

Security & Surveillance

Real-time anomaly detection, crowd behavior analysis, and perimeter monitoring with configurable alert triggers.

Creative & Marketing AI

Brand-consistent image generation, automated ad creative production, and visual content at 10x the speed of traditional photography.

Agriculture & Environment

Crop disease detection from drone imagery, yield estimation, and environmental monitoring using satellite and aerial CV.

98.5%
Detection accuracy
<50ms
Edge inference latency
10x
Faster visual content creation
120fps
Real-time video processing

Best-in-class tools for
every visual task

YOLOv9
Stable Diffusion
SAM 2
DALL·E
OpenCV
TensorRT
PyTorch
ONNX
ControlNet
Mask R-CNN
InsightFace
ByteTrack

From dataset to
deployed model

01
Dataset Collection & Annotation

We build or curate annotated image and video datasets tailored to your visual domain — including synthetic augmentation when real data is scarce.

02
Model Architecture Selection & Training

We select and customize the right architecture for your task — detection, segmentation, generation, or classification — with distributed training for large datasets.

03
Optimization & Quantization

We apply TensorRT compilation, INT8 quantization, and model pruning to hit your latency targets — whether you're on cloud GPUs or edge silicon.

04
Edge or Cloud Deployment

Deploy via REST API, SDK, RTSP stream integration, or embedded on NVIDIA Jetson or Intel OpenVINO — with monitoring and retraining pipelines included.

Ready to build visual AI that actually sees?

Tell us your use case, your deployment target, and your accuracy requirements. We'll design the right system.

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