You will get Car Damage Detection System using Deep Learning & Computer Vision
Project details
We specialize in delivering production-grade AI solutions for the automotive industry. my team has successfully deployed computer vision models for vehicle inspection systems, achieving 90%+ accuracy in real-world conditions. For this car damage detection Proof of Concept (POC) , we bring expertise in deep learning architectures (CNNs, Transfer Learning with ResNet/EfficientNet), proven Streamlit development experience, and a track record of meeting tight deadlines. What sets us apart: we don't just deliver a model—we provide a fully functional, deployable solution with clean code, comprehensive documentation, and ongoing support to ensure your Proof of Concept (POC) transitions smoothly into production.
Machine Learning Tools
Python, Python Scikit-Learn, PyTorchWhat's included
| Service Tiers |
Starter
$250
|
Standard
$550
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 30 days | 21 days | 14 days |
Number of Revisions | 2 | 5 | 9 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
About VishnuVardhan
AI Engineer | Computer Vision & RAG/NLP Specialist
100%
Job Success
Hyderabad, India - 2:22 am local time
I build production grade computer vision and live video analytics systems along with detection, segmentation, classification, tracking, and real-time inference that work in real-world workflows, not just notebook prototypes.
With 4+ years of experience across Machine Learning, Computer Vision, NLP, and Cloud AI, I develop systems that work with images, videos, live streams, and business data from data preparation and model training to production integration and deployment.
My Computer Vision work includes object detection, instance and semantic segmentation, classification, object tracking, automated annotation, and live video analytics using YOLO, YOLOv8, YOLOv11, PyTorch, Python, OpenCV, CVAT, and Roboflow.
I have built live video analytics pipelines that process incoming video streams, run computer vision inference on video frames, extract visual information, and generate analytics for downstream workflows. This includes real-time frame processing, detection and segmentation, tracking across frames, and video-based visual analysis.
On the Generative AI side, I build RAG systems, AI agents, enterprise knowledge assistants, conversational AI applications, and workflow automation using modern LLM technologies.
Recent production work:
98% Dice score on brain tumor segmentation (MRI) using U-Net, RAAGR2-Net, DeepLabV3, and SegFormer—from scratch in PyTorch (benchmarking for clinical accuracy).
95% accuracy car damage classifier deployed on VROOM Cars (production environment).
92% top-1 accuracy food classifier across 101 categories via ViT fine-tuning.
RAG chatbot that reduced support workload by 27% using PDF knowledge bases, ChromaDB, and FastAPI.
SERVICES
✅ AI Data Annotation & Labeling
MRI, video, and image annotation for computer vision pipelines — bounding boxes, semantic masks, and clinical labeling using LabelStudio, Roboflow, and CVAT. Medical-grade accuracy for production pipelines.
✅Computer Vision and Live Video Analytics
1. Object detection and image segmentation.
2. YOLO, YOLOv8, and YOLOv11 solutions.
3. Instance and semantic segmentation.
4. Real-time live video analytics.
5. RTSP, webcam, recorded-video, and stream processing.
6. Frame-level inference and video preprocessing.
7. Object detection and tracking across video frames.
8. People, vehicle, product, and asset monitoring.
9. Video-based visual analytics.
10.Automated image and video annotation.
11. AI-assisted auto-labeling pipelines.
12. Model training, fine-tuning, and error analysis.
13. Inference optimization and production integration.
✅ AI Agents & Agentic Workflows
1. Single-Agent & Multi-Agent Systems
2. LangGraph Agent Development
3. MCP (Model Context Protocol) Integrations
4. Tool Calling & Function Calling Agents
5. Autonomous Research & Task Execution Agents
6. AI Workflow Automation
✅ RAG & Enterprise Search
1. Retrieval-Augmented Generation (RAG)
2. Enterprise Knowledge Assistants
3. Internal Documentation Chatbots
4. PDF, SharePoint, Confluence & Website Search
5. Hybrid Search (Vector + Keyword)
6. Agentic RAG Architectures
✅ Conversational AI & Voice AI
1. AI Chatbots
2. Customer Support Assistants
3. AI Voice Agents
4. Call Center Automation
5. Real-Time Speech-to-Speech Applications
6. Voice Ordering & Appointment Booking Systems
𝗟𝗘𝗧'𝗦 𝗖𝗢𝗟𝗟𝗔𝗕𝗢𝗥𝗔𝗧𝗘:
✅ Every deliverable includes 10 days of post-delivery support — no one-off fixes
✅ Available 50+ hours/week with a 4-hour response guarantee
✅ All systems are production-deployed, not notebook experiments
Send your project details and I will respond within 4 hours with a clear technical approach and timeline.
Steps for completing your project
After purchasing the project, send requirements so VishnuVardhan can start the project.
Delivery time starts when VishnuVardhan receives requirements from you.
VishnuVardhan works on your project following the steps below.
Revisions may occur after the delivery date.
Problem Statement
explain problem statement clearly then moves to next step