You will get pretrained/customized object detection/image segmentation solution
Top Rated
Top Rated
Project details
You will get an object detection/semantic segmentation/instance segmentation/panoptic segmentation solution using a pre-trained model. Additionally, you can give your own dataset, I'll use it to fine-tune the model using transfer learning.
From start to end, you won't have to worry about a thing. With over 3 years of python scripting experience, I am able to break down complex tasks into tangible deliverables that we'll work together to achieve. I will also optimize the model to run well on the user-end, be it nvidia gpu, intel or arm processor or a mobile device. With me you can always set the bar high, and I'll do my best to achieve it.
If you like my project, let's continue our discussion on the chat!
Thanks!
From start to end, you won't have to worry about a thing. With over 3 years of python scripting experience, I am able to break down complex tasks into tangible deliverables that we'll work together to achieve. I will also optimize the model to run well on the user-end, be it nvidia gpu, intel or arm processor or a mobile device. With me you can always set the bar high, and I'll do my best to achieve it.
If you like my project, let's continue our discussion on the chat!
Thanks!
Machine Learning Tools
pandas, Python, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$50
|
Standard
$100
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 30 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 1 | 2 | 1 |
Number of Scenarios | 2 | 2 | 4 |
Number of Graphs/Charts | 2 | 4 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $150
Additional Revision
+$30
Additional Model Variation
(+ 3 Days)
+$40
Additional Scenario
(+ 3 Days)
+$40
Model Documentation
(+ 1 Day)
+$20Frequently asked questions
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About Muhammad Abdullah
Senior Computer Vision & ML Consultant | Triton | PyTorch | Postgres
100%
Job Success
Rawalpindi, Pakistan - 2:03 pm local time
𝐍𝐨𝐭𝐜𝐡𝐚 𝐀𝐯𝐞𝐫𝐚𝐠𝐞 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐆𝐮𝐲 😎
I don’t stop at a cool demo. Shipping LootMart (hyper-local marketplace) taught me the full stack around models: clean APIs, rock-solid data contracts, observability, security, and predictable costs. That’s why my CV/ML services behave like products, not science projects.
𝐖𝐡𝐚𝐭 𝐈 𝐀𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐃𝐨
- Computer Vision & Video Analytics (2D/3D): detection (YOLO/DETR), multi-object tracking (ByteTrack/DeepSORT), segmentation (U-Net), OCR/document AI, pose/re-ID, visual search & face/product matching (Siamese + Triplet Loss), point clouds & geometry.
- High-Throughput Inference: NVIDIA Triton (dynamic batching, concurrent models, HTTP/gRPC), TensorRT (FP16), ONNX Runtime; autoscaling containers with health checks and graceful rollouts.
- Robust Ingestion: multi-RTSP pipelines with back-pressure control using OpenCV, FFmpeg, PyAV/decord so frames don’t mysteriously vanish under load.
- MLOps & Services: FastAPI/Flask gateways, worker queues, CI/CD, Docker + Nginx; W&B for experiments; versioned datasets; reproducible training.
- Data & Integrations: Postgres (schema design, RLS, SQL/PLpgSQL), Redis, vector DBs (Milvus/Qdrant), webhook-driven architectures, n8n workflows for ETL/alerts, and MCP (Model Context Protocol) to wire AI tools into your internal systems.
- Selective Full-Stack Glue (when it helps): Next.js app layers, secure webhooks, auth, real-time updates, and crisp dashboards so stakeholders can see impact.
𝐏𝐫𝐨𝐨𝐟 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐮𝐝𝐝𝐢𝐧𝐠 (𝐑𝐞𝐜𝐞𝐧𝐭 𝐖𝐢𝐧𝐬)
1. Triton-backed real-time CCTV analytics across multiple cameras on commodity GPUs (dynamic batching = buttery latency).
2. Visual matching pipelines (Siamese/Triplet) for search/dedupe with rigorous evals and W&B tracking.
3. Heavy research models → ONNX/TensorRT → low-latency services that actually survive production traffic.
4. Production plumbing that lasts: Postgres-first data contracts, webhook fan-out, n8n automations... no brittle glue.
𝐇𝐨𝐰 𝐖𝐞’𝐥𝐥 𝐖𝐨𝐫𝐤 (𝐑𝐎𝐈 𝐅𝐢𝐫𝐬𝐭, 𝐀𝐥𝐰𝐚𝐲𝐬)
1. 30-min discovery → lock in the KPI (latency, accuracy, throughput, cost).
2. Roadmap & estimate → phases, risks, acceptance tests.
3. Build & validate → baselines first, then iterate; measurable deltas each milestone.
4. Handoff & scale → docs, runbooks, and knowledge transfer so your team owns it.
𝐂𝐨𝐫𝐞 𝐒𝐭𝐚𝐜𝐤
Python • PyTorch • TensorRT • ONNX Runtime • NVIDIA Triton • OpenCV • Kornia • FFmpeg • PyAV/decord • Postgres • Redis • Milvus/Qdrant • FastAPI/Flask • Next.js • Docker • Nginx • Weights & Biases • Webhooks • n8n • MCP
𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲
Consulting/part-time (fractional) engagements: architecture reviews, performance tuning, prototypes, or owning a CV/ML workstream. Top-rated on Upwork. Minimum $100/hr.
If you want production-ready computer vision, real-time video, reliable pipelines, and clear ROI, 𝐥𝐞𝐭’𝐬 𝐭𝐚𝐥𝐤. I’ll map your goal to a pragmatic plan and ship results you can measure.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Abdullah can start the project.
Delivery time starts when Muhammad Abdullah receives requirements from you.
Muhammad Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Work on developing the customized solution/training the model