test with a readme
Browse files- dnn-roi/pdhd/20260601/README.md +125 -0
dnn-roi/pdhd/20260601/README.md
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# PDHD MobileNetV3-UNet baseline ROI models
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## Author
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Hokyeong Nam, gkddk33@gmail.com
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## Description
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This document records the CVMFS README metadata for three TorchScript
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**MobileNetV3-UNet baseline** DNN-ROI models trained for ProtoDUNE-HD (PDHD)
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signal-processing studies. It summarizes the training and preprocessing choices
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needed by DUNE/Wire-Cell users to select and configure the correct model.
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## Model files
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| File | Architecture | Training events | Time rebin | Truth threshold | Truth padding | Training planes | Input channels |
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| --- | --- | ---: | ---: | ---: | --- | --- | ---: |
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| `mobileunetv3-cosmic590-deposplat-pdhd-rebin6-pad1-uv.ts` | MobileNetV3-UNet baseline | 590 | 6 | 100 | enabled | U + V | 3 |
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| `mobileunetv3-cosmic590-deposplat-pdhd-rebin4-pad1-uv.ts` | MobileNetV3-UNet baseline | 590 | 4 | 100 | enabled | U + V | 3 |
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| `mobileunetv3-cosmic590-deposplat-pdhd-rebin10-pad0-uv.ts` | MobileNetV3-UNet baseline | 590 | 10 | 100 | disabled | U + V | 3 |
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The filename tokens encode the model family, training/data variant, detector
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sample, time-rebinning configuration, truth-label padding configuration, and
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training plane set.
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## Training and preprocessing metadata
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All three models were produced with the same baseline workflow except for the
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`rebin` and padding choices listed above.
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### Detector sample, planes, and event count
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- Training sample: **PDHD** training sample.
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- Number of training events: **590**.
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- Planes used for training: **U plane and V plane only** (`UV`).
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- The models were trained as per-plane ROI predictors; the collection plane was
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not included in this model set.
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### Input tensor
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The network input has **three channels**:
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1. `loose_lf`
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2. `mp2_roi`
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3. `mp3_roi`
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When connecting these models in a Wire-Cell graph, make sure the three input
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frames/tensors are supplied to the model.
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### Truth-label construction
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- Truth source: PDHD truth/deposition image used by the baseline preprocessing.
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- Truth threshold: `100` for all three models.
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- Thresholding was applied consistently for U-plane and V-plane training samples.
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### Padding configuration
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The rebin-4 and rebin-6 models use padded truth labels:
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```text
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padding = 1
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padding_side = both
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min_run = 1
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avoid_merge = enabled
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```
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The rebin-10 model does **not** add extra padding to the truth labels:
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```text
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padding = 0
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```
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## Choosing a model
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Use the model whose `rebin` value matches the preprocessing expected by the
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Wire-Cell deployment or validation chain:
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- Use `mobileunetv3-cosmic590-deposplat-pdhd-rebin4-pad1-uv.ts` for rebin-4 input.
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- Use `mobileunetv3-cosmic590-deposplat-pdhd-rebin6-pad1-uv.ts` for rebin-6 input.
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- Use `mobileunetv3-cosmic590-deposplat-pdhd-rebin10-pad0-uv.ts` for rebin-10 input.
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Do not mix a model with a different time-rebinning configuration unless the
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consumer explicitly converts the input tensors to the model's training binning.
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## Expected inference contract
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- Format: PyTorch TorchScript (`.ts`).
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- Model family: MobileNetV3 encoder with U-Net-style decoder.
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- Inputs: one batch of three-channel ROI/SP feature images.
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- Output: one ROI probability/mask image in the corresponding rebinned time
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coordinate system.
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## Minimal provenance record
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```yaml
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model_family: MobileNetV3-UNet baseline
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format: torchscript
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sample: PDHD
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training_events: 590
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training_variant: cosmic590-deposplat
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planes: [U, V]
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input_channels: [loose_lf, mp2_roi, mp3_roi]
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truth_threshold: 100
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models:
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- file: mobileunetv3-cosmic590-deposplat-pdhd-rebin6-pad1-uv.ts
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rebin: 6
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padding:
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enabled: true
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padding: 1
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padding_side: both
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min_run: 1
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avoid_merge: true
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- file: mobileunetv3-cosmic590-deposplat-pdhd-rebin4-pad1-uv.ts
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rebin: 4
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padding:
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enabled: true
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padding: 1
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padding_side: both
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min_run: 1
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avoid_merge: true
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- file: mobileunetv3-cosmic590-deposplat-pdhd-rebin10-pad0-uv.ts
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rebin: 10
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padding:
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enabled: false
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padding: 0
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```
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