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You will get Custom Computer Vision & OCR Pipelines for Images (OCR, Object Detection)
Project details
This project delivers a production‑ready Computer Vision and Document AI pipeline that automates OCR, object detection, segmentation, and diagram understanding for your real‑world documents and images. It is built for teams that want to turn invoices, forms, contracts, PDFs, scans, UI screenshots, and technical diagrams into clean, structured data.
Using modern deep learning models (YOLOv8, RF‑DETR, SAM‑style segmentation, PaddleOCR) with Python, OpenCV, and FastAPI/Flask, you get high‑accuracy document processing and image processing wrapped in simple REST APIs or microservices. The solution supports key use cases like invoice processing, form recognition, ID / receipt parsing, table extraction, and diagram or flowchart parsing with arrow‑to‑node association.
Everything is designed to be production‑ready: Dockerized services, cloud‑ready deployment on AWS/GCP/Azure, and a clean architecture that fits into SaaS products or internal automation tools. Whether you need a focused computer vision/OCR model or a full end‑to‑end Document AI system, you get a custom pipeline aligned with your data, your business rules, and your existing stack.
Using modern deep learning models (YOLOv8, RF‑DETR, SAM‑style segmentation, PaddleOCR) with Python, OpenCV, and FastAPI/Flask, you get high‑accuracy document processing and image processing wrapped in simple REST APIs or microservices. The solution supports key use cases like invoice processing, form recognition, ID / receipt parsing, table extraction, and diagram or flowchart parsing with arrow‑to‑node association.
Everything is designed to be production‑ready: Dockerized services, cloud‑ready deployment on AWS/GCP/Azure, and a clean architecture that fits into SaaS products or internal automation tools. Whether you need a focused computer vision/OCR model or a full end‑to‑end Document AI system, you get a custom pipeline aligned with your data, your business rules, and your existing stack.
Machine Learning Tools
Amazon SageMaker, BERT, GPT-3, Keras, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$150
|
Standard
$450
|
Advanced
$850
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 3 | 6 | Unlimited |
Number of Model Variations | 3 | 5 | 10 |
Number of Scenarios | 3 | 7 | 12 |
Number of Graphs/Charts | 20 | 50 | 0 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100
Additional Model Variation
+$100About Wasif
AI & Full-Stack Developer | React, Next.js, Node.js, Python & WebRTC
Lahore, Pakistan - 12:33 am local time
Proven Results
Diagram Understanding Engine
Built a computer vision system using RF-DETR, SAM-style segmentation, and OCR to parse complex technical diagrams. Achieved 0.83 mAP and 97% arrow-to-node accuracy across diverse layouts.
Conversational AI Agents
Designed and deployed LLM-based assistants using Amazon Lex, Bedrock, and AWS Lambda, fine-tuned on domain data to deliver secure, low-latency production chat systems.
AI Career Recommendation Engine
Built a RAG-powered recommendation system using vector databases and scraped job-market data, achieving ~89% match accuracy in internal evaluations.
Sign Language Recognition System
Implemented a real-time deep learning pipeline for gesture recognition to support assistive communication use cases.
What I Build
Custom Computer Vision Systems
Diagram/flowchart understanding, document AI, detection and segmentation, OCR pipelines, and structured post-processing.
LLM Products & AI Agents
Domain chatbots, internal copilots, RAG over your data, and multi-step agents that securely call your APIs.
Full-Stack AI Applications
React/Next.js frontends with Node.js or FastAPI backends, authentication, dashboards, admin panels, deployed on AWS, Azure, or Vercel.
Data & ML Pipelines
Web scraping, ETL, feature engineering, forecasting models, and analytics dashboards using MongoDB/PostgreSQL and cloud storage.
How I Work
Architecture-first — Clear system design before coding (data flows, APIs, infrastructure).
Milestone-driven delivery — Small, shippable phases with visible progress.
Clean, maintainable code — Structured repos, environment configs, and documentation.
Transparent communication — Fast responses, clear timelines, no surprises.
I’m ready to help you move from idea to a scalable production system. If you want someone who can handle AI, backend systems, and full-stack delivery end-to-end, send a short project summary and I’ll reply with a proposed architecture and milestones tailored to your goals.
Steps for completing your project
After purchasing the project, send requirements so Wasif can start the project.
Delivery time starts when Wasif receives requirements from you.
Wasif works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1 – Requirements & sample data
You share 2–3 sample documents/images (PDFs, scans, diagrams) and describe which fields, objects, or relationships you want the system to detect or extract.
Step 2 – Solution design & model selection
A custom Computer Vision / Document AI pipeline is designed for your use case, selecting suitable models (YOLOv8, RF‑DETR, SAM‑style segmentation, PaddleOCR) plus post‑processing and validation logic.