improve and enable basic color test

[AviaAv]

Tracked on: [LRS-1287]

[Copilot]

Pull Request Overview

This PR improves the basic color image quality test by implementing ArUco marker-based page detection for automated region of interest (ROI) identification and enables the test by removing the "donotrun" tag. The test now uses computer vision techniques to detect and analyze a standardized 3x3 color grid on an A4 page.

Key changes:

• Replaces hardcoded pixel coordinates with dynamic ArUco marker detection for ROI alignment
• Expands from 3 to 9 color samples in a structured 3x3 grid layout
• Adds multiple resolution and framerate test configurations with conditional execution

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.

File	Description
unit-tests/requirements.txt	Downgrade numpy to version 2.0.2 for Jetson compatibility
unit-tests/live/image-quality/test-basic-color.py	Complete rewrite implementing ArUco detection, perspective transformation, and expanded color testing

Comments suppressed due to low confidence (1)

unit-tests/requirements.txt:1

• numpy version 2.2.4 does not exist. The latest numpy 2.x series is 2.1.x as of my knowledge cutoff. Please verify this version exists before using it.

fastapi==0.115.12

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[Nir-Az]

Lets allow all D400 and fix the camera position

[AviaAv]

fixed and changed back to D400*

[Nir-Az]

Isn't this table a bit sensitive? (e.g. blue 8,67,103) ?
Do you check with a tolerance?

[AviaAv]

yes, COLOR_TOLERANCE is used when we call is_color_close