Add script to write brightfield reference inputs and prediction targets

[wli51]

Summary by CodeRabbit

• New Features
  • Added generation of normalized brightfield reference inputs and target-channel datasets from validated imaging data.
  • Supports 256-pixel object-containing image crops with configurable, reproducible subsampling per plate and well.
  • Includes specialized normalization for OrigAGP target data and standard normalization for other channels.
• Validation
  • Added checks for required files, metadata, directories, and source-image provenance to ensure generated datasets are complete and traceable.

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⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Advanced

Run ID: 93a468ce-a108-48ef-a9fe-2be8336c28cb

📥 Commits

Reviewing files that changed from the base of the PR and between 012f667 and 43e7a9f.

📒 Files selected for processing (3)

• 3.model_eval/3.0.write_model_input_target.ipynb
• 3.model_eval/nbconverted/3.0.write_model_input_target.py
• utils/write_reference_image.py

📝 Walkthrough

Walkthrough

The new executable script validates configuration and input data, builds sampled 256-pixel image crops for two plates, validates crop provenance, and writes normalized brightfield reference and target records.

Changes

Model input and target generation

Layer / File(s)	Summary
Configuration and metadata discovery 3.model_eval/nbconverted/3.0.write_model_input_target.py	The script validates required paths, loads processed loaddata, restricts records to two plates, and loads shared profile metadata.
Crop construction and sampling 3.model_eval/nbconverted/3.0.write_model_input_target.py	The script creates object-containing 256-pixel crops, validates source-file provenance, normalizes paths, and applies seeded per-well and per-plate subsampling.
Reference and target record output 3.model_eval/nbconverted/3.0.write_model_input_target.py	The script writes normalized input-channel reference records and channel-specific target records. OrigAGP uses quarter-16-bit normalization. Other channels use standard 16-bit normalization.

Priority: ⬇️ Low

Estimated code review effort: 3 (Moderate) | ~25 minutes

Change: Feature

Sequence Diagram(s)

sequenceDiagram
  participant Configuration
  participant ProcessedLoaddata
  participant ImageDataset
  participant CropSampler
  participant LanceOutput
  Configuration->>ProcessedLoaddata: Load validated configuration and plate metadata
  ProcessedLoaddata->>ImageDataset: Build the multi-channel image dataset
  ImageDataset->>CropSampler: Generate object-containing 256-pixel crops
  CropSampler->>CropSampler: Validate provenance and apply seeded sampling
  CropSampler->>LanceOutput: Write normalized reference and target records

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Merge Risk: 🟠 High · up to 012f6

The script can produce incorrectly labeled reference and target records during ordinary subsampling, so the dataset-index alignment should be fixed before merge.

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and concisely describes the main change: adding a script that writes brightfield reference inputs and prediction targets.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. Docstring coverage is scoped to functions touched by this diff. Analyzed 0 functions across 1…
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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• Create PR with unit tests

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Actionable comments posted: 1

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Inline comments:
In `@3.model_eval/nbconverted/3.0.write_model_input_target.py`:
- Line 221: Update the write_reference_images call to pass
crop_index_sampled["dataset_index"].to_numpy(), then modify
write_reference_images to use dataset_indices[i] instead of i when reading
dataset entries for both the reference and every target-channel call.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Advanced

Run ID: 939cabd4-c8e9-4c3b-8e0d-e2a985802d1c

📥 Commits

Reviewing files that changed from the base of the PR and between 5220f11 and 012f667.

📒 Files selected for processing (2)

• 3.model_eval/3.0.write_model_input_target.ipynb
• 3.model_eval/nbconverted/3.0.write_model_input_target.py

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