fix: slice numpy array values in custom_data per row in CSVSink and J…

[farukalamai]

Before submitting

• Self-reviewed the code
• Updated documentation, follow Google-style
• Added docs entry for autogeneration (if new functions/classes)
• Added/updated tests
• All tests pass locally

Description

Fixes a bug in CSVSink and JSONSink where passing a numpy array as a
custom_data value wrote the entire array on every row instead of the
per-detection scalar value.

Type of Change

• 🐛 Bug fix (non-breaking change which fixes an issue)

Motivation and Context

When users pass computed per-detection values like detections.area via
custom_data, each row should receive its own scalar — not the whole array.

# Before (broken): every row got the full array
with sv.CSVSink("out.csv") as sink:
    sink.append(detections, custom_data={"area": detections.area})
# area column: [400.0, 400.0] on every row ❌

# After (fixed): each row gets its own value
# area column: 400.0, 400.0 ✅

The root cause was row.update(custom_data) inside the per-detection loop,
which blindly wrote the whole value. The fix applies the same per-index
slicing logic that detections.data already uses correctly.

Closes #1397

Changes Made

• src/supervision/detection/tools/csv_sink.py — slice numpy array values in custom_data per detection row
• src/supervision/detection/tools/json_sink.py — same fix
• tests/detection/test_csv.py — added test case for numpy array in custom_data

Testing

• I have tested this code locally
• I have added unit tests that prove my fix is effective or that my feature works
• All new and existing tests pass

Google Colab (optional)

Colab link:

Screenshots/Videos (optional)

Additional Notes

The fix is backward compatible — scalar values in custom_data (e.g.
{"frame_number": 42}) continue to work as before, written as-is on every
row.