Computer Vision
Detection and image-analysis apps that watch camera feeds or images and raise alerts automatically.
Overview
I build computer-vision applications for healthcare, public safety and transport. A model watches a camera feed or analyses an uploaded image, and a Django backend raises the alert, logs the incident and shows the result, so the detection leads to action.
What you get
Real-time detection systems, such as road accident and smoking detection
Instant alert notifications with location or incident details
Automatic incident logging and records stored in the Django backend
Medical image analysis, such as early-stage foot ulcer screening with results and recommendations
Reports and analytics to review incidents over time
How we work together
- 1
Use case and input
We agree what must be detected and what camera, sensor or image input is available.
- 2
Model integration
A computer-vision or medical-imaging model is connected to the application.
- 3
Alerts and logging
The backend triggers notifications and records every incident automatically.
- 4
Testing
Checks on detection behaviour and on the alert and logging flow.
- 5
Deployment
The system is deployed and handed over with its source and setup notes.
Technology stack
Computer Vision
detection from camera, sensor and image data
Medical Imaging AI
image analysis for screening
Python
model integration and application logic
Django
backend, alerts and incident logging
MySQL
database
Git
version control
Good fit for
Reference screenshots
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