Python Script (OOP) for Video noise and sharpness quantification

I'm looking for a seasoned Python developer with specific experience in image especially video analysis to create a script that can process a full mp4 video and identify the positions of noise in the video. The idea is to scan the video, locate identify the different type of noises and their value and externalize this findings into a json file

Key Requirements:

- The script (OOP based) should be able to read a video in mp4, mkv, mov format.
- The library used for reading the video is not fixed. You can choose from libraries like (e.g. OpenCV, PyAV, or MoviePy, but the solution should be compatible with both Windows and Linux (and mac)
- The output should have details of the signal, the different type noises, the common ratios and finally the values
... - the frame number
... - the time position/time code
... - the data detected
...... - e.g. the sharpness
and this should be outputed in a JSON file per video file.

Ideal Skillset:

- Proficiency in Python
- Experience with video processing libraries (like OpenCV, PyAV, or MoviePy)
- Experiences with OOP (classes and lists)
- Familiarity with JSON output format.


Milestones:

MS1:
provide python OOP module to measure the blurness & sharpness quantification of images and videos
data will be written in same filename but with .json as extension
we will share you testing images and videos
2 modes required
- demo mode with showing the video+persisting the demo video
- performance mode, which only processes the data

MS2
same as MS1, except now you extract the different noises from the image. Also as json

MS3
now detect faces and identify the noises and sharpness/bluryness of the faces. Also as json

MS4:
rest will be discusses and agreed mutually


Budget?
will not be disclosed, place your best bid to get considered

Payment?
- you estimate in a WBS (optimistic, expected, pessimistic, where optimistic < expected < pessimistic) after getting the task
- we discuss about clearances and effort
- we mutually agree to effort
- we assign you the task after mutually agreed
- you implement, test and deliver
- you provide also unit /integration tests to ensure code is always working
- you document each required step to make interaction of systems to work
- we test on our premise (you maybe help to fix issues)
- we pay
(basically the rules of freelancer)

Closed book vs open book?
We work only on open book.
Closed book means you are unwilling to define a WBS for the work and you add only a price tag to the task.
We are sorry we will not hire you in such a case!

documentation requirements:
- well structured
- reproducible steps for others
- spell & grammar checked

coding requirements:
- clean code in terms of clean code book
- best practices for development (code level documentation, common patterns, OOP as possible)
- best practices for agreed and choosen libs/frameworks
- classes are reusable for later extensions and reuse options (after MS4)

Deliveries?
- in our on premise git (access will be granted to you)
- full sources (NO! Jupyter Notebook)
- multiple samples of videos will be shared via URL to download
- bash to build & run your code
- poetry build
- latest stable python version
- libs, need prior confirm and we prefer to use mostly latest stable versions
- your code is working on our end too
- your code passes our CI build (with provided maven pom.xml can be checked)
- you may require to help us here on setup
- we require, depending on availability and on complexity 2-4 weeks test time per milestone. Usually clearly less