LUMEN - Full Stack Image Data Analyzer (will share the link after completing)

It's primarily a learning project, not a platform/SaaS or something.

The basic idea: The basic idea is simple: give LUMEN an image, and it extracts different properties from it and stores the analysis as structured data.

Working: The image is first loaded using PIL and converted into a NumPy array. LUMEN then performs different types of analysis, including:

• Image dimensions

• dtype, std

• min/max, mean

• RGB channel statistics

• Histograms and intensity distribution

• Perceptual brightness

• Contrast, Sharpness / blur

• Colorfulness, Dominant colors

• Exposure, Entropy

• Duplicate detection

For duplicate detection, I use SHA-256 hashing. The image is hashed and the resulting hash can be used to identify identical files and group duplicates.

Also using pytest to test the analysis functions.

Database side - Made a persistence layer using PostgreSQL + SQLAlchemy. The idea is to store the analyzed images and their results as structured records.

For example, an image can have information such as:

• ID

• filename

• dimensions

• file information

• analysis timestamp

And the analysis can contain things like:

• mean brightness

• standard deviation

• minimum / maximum values

• RGB channel statistics

• quality metrics

SQLAlchemy ORM is used to represent DB tables as Python models.

Backend — (Work in progress) The backend is being built with FastAPI,

FastAPI receives the image/request, the analysis engine processes it and the results are validated and structured, and the relevant data is persisted in PostgreSQL.

And the frontend will be made later and then deployment......✌🏼

Still work in progress, but this is where LUMEN is currently at, rn making the backend part :)