Detect. Interpret. Enhance.

Computer Vision Solutions

Retrieve real-time insights from images and videos through computer vision development services that turn pixels into powerful predictions.
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Computer Vision Development Services

Object Detection

Detect and localize objects in images or videos using advanced models like YOLOv8, YOLO11, and Vision Transformers (ViTs). These models generate bounding boxes, assign labels, and utilize a self-attention mechanism to capture global context, enhancing accuracy. Businesses can use our computer vision services for object detection, inventory tracking, and automated monitoring.

Object Detection
Object Tracking

Object Tracking

SOTA video analysis models like ByteTrack, DeepSORT, ETTrack, and OneTracker are best for object tracking and scene understanding. These models accurately track objects across frames, detect motion, and predict future movements. After analyzing object interactions and recognizing anomalies, they can trigger actions such as alerts or emergency responses, making them useful for applications like action recognition, vehicle tracking, and behavior analysis.

Instance Segmentation

Instance segmentation identifies and segments individual objects within an image. We deploy advanced models like YOLO11-seg, Mask R-CNN, SAM2, OneFormer, and SOTA to generate precise masks for each object. For pixel-level precision, we use semantic segmentation models like DeepLabV3+ and SegFormer. Works best for medical imaging and autonomous navigation.

Visual Search

Visual Search

Customers often seek to find similar products, objects, or relevant information by simply uploading a picture or a video clip. Using advanced models like CLIP, DETR, and YOLO11, we enable accurate product recognition and retrieval based on images. This technology has applications in e-commerce, retail, fashion, and catalog management, making it easier for customers to find what they need.

Pose Estimation

Imagine being able to track and understand human movements, gestures, and body positions with pinpoint accuracy. Our pose estimation technology, powered by models like YOLO-pose, OpenPose, and HRNet, makes this possible in real-time. Optimize fitness tracking, virtual experiences, and workplace ergonomics to learn how people move and interact.

Pose estimation
Classification

Classification

We build custom image classification models using advanced architectures like EfficientNet and Vision Transformers (ViT). Our models are optimized for accuracy and speed, making them suitable for real-time applications like medical diagnostics, defect detection, and inventory management. We also offer on-device classification solutions for IoT and mobile devices.

Visual Language Models (VLMs)

VLMs work by combining visual information with text, helping computers ‘see’ and talk about what they see. It’s a collaboration of NLP and computer vision for tasks like image captioning, generating answers, and summarizing visual data. Using advanced  VLMs like Llama-3.2-90B-Vision-Instruct, InternVL2.5, Qwen2-VL, CogVLM2, and PaliGemma2, we enable accurate image analysis.

Visual Language Models
Facial Recognition

Facial Recognition

VisionX’s facial recognition solutions, powered by advanced models like FaceNet, ArcFace, and YOLOv11-face, deliver high-accuracy identification and verification. Ideal for security, access control, and marketing, facial recognition services deliver real-time recognition while adhering to GDPR standards. Our models are customizable to meet specific business needs.

OCR Extraction

If your business relies on visual data, CV-powered OCR models like PaddleOCR, EasyOCR, and Tesseract can do wonders. They extract text from scanned documents, video frames, and real-time streams while accurately processing forms, receipts, and tables. We customize OCR models for your specific needs, like document scanning, inventory management, and real-time video text extraction.

OCR Extraction

Computer Vision Development Process

Our 5-step approach to computer vision development services:

01

Data Collection & Annotation

We collaborate with clients to collect images and videos from cameras, databases, or online sources. Tools such as OpenCV (latest version) and PIL refine image quality by addressing challenges like poor lighting, noise, and low resolution. Additional techniques like histogram equalization and edge enhancement can further optimize the data for the next stages in the pipeline.

02

Model Selection & Customization

We carefully select and fine-tune models based on your requirements using frameworks like PyTorch, TensorFlow, and Keras. If necessary, we develop custom neural networks to achieve the best results for your business needs.

03

Training & Optimization

We train models on high-performance GPUs, using advanced techniques like data augmentation and hyperparameter tuning to optimize for speed, accuracy, and reliability.

04

Deployment

Our computer vision solutions are deployed across multiple environments, such as cloud platforms (AWS, Azure, GCP), on-premise systems, or edge devices. These models work for real-time processing and smoothly integrate with your existing infrastructure.

05

Continuous Monitoring & MLOps

We use tools like MLflow and Kubeflow to automate and scale the entire lifecycle of model development and deployment. This guarantees long-term performance and adaptability.

Why VisionX?

See Why Customers Love VisionX

FAQs

What is Computer Vision (CV)?

Computer Vision is the branch of AI that allows computers to understand the context of images and videos like NLP does for textual data. In simple words, computer vision solutions mimic human vision by processing and extracting information from visual data (images and videos), just like the human eye.

Computer vision allows computers to “see” images and videos. It works by breaking down images into numbers and then using algorithms to understand these numbers, performing tasks like face recognition or tracking objects. This is best for applications in which visual data is involved, such as self-driving cars and medical image analysis.

Computer Vision services include image classification, where images are categorized into predefined classes; object detection, which identifies and locates objects within images; and face recognition, used for identification and security.

No, computer vision and deep learning are not the same. Computer vision is a broader field that involves enabling computers to understand visual information. Deep learning is a specific technique within computer vision that uses artificial neural networks to learn complex patterns from data.

Some major algorithms are Convolutional Neural Networks (CNNs) for image recognition, Scale-Invariant Feature Transform (SIFT) for image matching, Histogram of Oriented Gradients (HOG) for object detection, and Optical Flow for motion estimation. VisionX is a computer vision development company that possesses expertise in all major algorithms.

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