33 lines
1.3 KiB
Markdown
33 lines
1.3 KiB
Markdown
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# Nuclei Counting and Segmentation
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This sample implements the [2018 Data Science Bowl challenge](https://www.kaggle.com/c/data-science-bowl-2018).
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The goal is to segment individual nuclei in microscopy images.
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The `nucleus.py` file contains the main parts of the code, and the two Jupyter notebooks
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## Command line Usage
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Train a new model starting from ImageNet weights using `train` dataset (which is `stage1_train` minus validation set)
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```
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python3 nucleus.py train --dataset=/path/to/dataset --subset=train --weights=imagenet
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```
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Train a new model starting from specific weights file using the full `stage1_train` dataset
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```
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python3 nucleus.py train --dataset=/path/to/dataset --subset=stage1_train --weights=/path/to/weights.h5
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```
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Resume training a model that you had trained earlier
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```
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python3 nucleus.py train --dataset=/path/to/dataset --subset=train --weights=last
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```
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Generate submission file from `stage1_test` images
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```
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python3 nucleus.py detect --dataset=/path/to/dataset --subset=stage1_test --weights=<last or /path/to/weights.h5>
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```
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## Jupyter notebooks
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Two Jupyter notebooks are provided as well: `inspect_nucleus_data.ipynb` and `inspect_nucleus_model.ipynb`.
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They explore the dataset, run stats on it, and go through the detection process step by step.
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