You will get full-fledged computer vision models
Project details
I build real-time fall detection using YOLOv8, deployed as a working web app — not just a trained model. You get detection on images, video, or live webcam, with visual alerts and downloadable results, ready to actually use.
Machine Learning Tools
ChatGPT, Google Sheets, MLflow, NLTK, NumPy, OpenCV, Python, PyTorch, scikit-learn, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$20
|
Standard
$30
|
Advanced
$40
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 2 days |
Number of Revisions | 7 | 9 | Unlimited |
Number of Model Variations | 3 | 5 | 5 |
Number of Scenarios | 2 | 4 | 6 |
Number of Graphs/Charts | 5 | 6 | 8 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$5
Additional Revision
+$2
Additional Model Variation
(+ 1 Day)
+$5
Additional Scenario
(+ 1 Day)
+$5
Additional Graph/Chart
(+ 1 Day)
+$3About Somaan
Data Scientist
Swat, Pakistan - 10:24 am local time
I build and deploy real-time computer vision applications — from model training to live web apps clients can actually use.
Recently shipped: a fall-detection system (YOLOv8s, 88% mAP50) deployed as a live Streamlit app with image/video/webcam support.
Stack: Python, OpenCV, YOLOv8, TensorFlow, Pandas, NumPy, SQL
What I offer:
Custom object detection/segmentation models trained on your data
End-to-end delivery: dataset prep → training → evaluation → deployed app
Clear, frequent updates — you'll never be guessing on project status
Drop a message and let's talk about what you're trying to build
Steps for completing your project
After purchasing the project, send requirements so Somaan can start the project.
Delivery time starts when Somaan receives requirements from you.
Somaan works on your project following the steps below.
Revisions may occur after the delivery date.
Deliver and explain
walkthrough + support for any questions