Revert add array to opencv

[ternaus]

Summary by Sourcery

Revert the addition of the add_array_simsimd function and refactor the add_opencv function for better handling of uint8 images with specific value types. Update benchmark results to use 500 images, providing a more comprehensive performance analysis across different operations and data types.

Enhancements:

• Refactor the add_opencv function to improve handling of uint8 images with negative scalar values or non-uint8 array values.

Tests:

• Update benchmark results to reflect performance changes with 500 images instead of 10, across various operations and data types.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR reverts changes to the OpenCV array addition implementation and updates benchmark results. The main change simplifies the conditional logic in the add_opencv function and removes the simsimd-based array addition implementation.

No diagrams generated as the changes look simple and do not need a visual representation.

File-Level Changes

Change	Details	Files
Simplified conditional logic in add_opencv function	Consolidated multiple if conditions into a single needs_float boolean variable Removed separate type-based conditional branches Simplified float32 conversion logic	albucore/functions.py
Removed simsimd-based array addition implementation	Removed conditional check for matching dtypes Removed call to add_array_simsimd function Defaulted to using add_opencv for all array additions	albucore/functions.py
Updated benchmark results with new measurements	Increased number of test images from 10 to 500 for more accurate results Updated performance metrics across all benchmark categories Updated package version from 0.0.17 to 0.0.19 Added new benchmark result files for various operations	benchmark/albucore_benchmark/results/uint8_1/*.md benchmark/albucore_benchmark/results/float32_1/*.md benchmark/albucore_benchmark/results/float32_3/*.md benchmark/albucore_benchmark/results/uint8_3/*.md

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Please upload report for BASE (main@8b309b4). Learn more about missing BASE report.

Additional details and impacted files

@@           Coverage Diff           @@
##             main      #43   +/-   ##
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  Coverage        ?   57.93%           
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  Files           ?       20           
  Lines           ?     2223           
  Branches        ?        0           
=======================================
  Hits            ?     1288           
  Misses          ?      935           
  Partials        ?        0           

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