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docs/examples/callbacks.ipynb

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"cells": [
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{
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"cell_type": "markdown",
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"id": "3982f572-4151-47df-923d-3cd6794e7070",
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"id": "0",
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"metadata": {},
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"source": [
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"# Callbacks\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "eebbcc16-dd8a-4e9b-9d79-b7cb2d3dbee0",
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"id": "1",
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{
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"cell_type": "code",
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"id": "f576ccc0-d8e8-4d6c-b09c-5c3634c94bf6",
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"id": "2",
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},
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{
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"cell_type": "markdown",
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"id": "3",
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"## Overlaying a mask\n",
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"id": "5",
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docs/examples/lazy-loading.ipynb

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"cells": [
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"id": "0",
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"metadata": {},
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"# Images from a function (Lazy loading)\n",
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{
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"cell_type": "code",
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"id": "1",
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"metadata": {},
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b62a762f-26be-4dba-ab07-ec26648b970b",
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"id": "2",
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docs/examples/multi-class.ipynb

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"cells": [
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"id": "0",
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"metadata": {},
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"# Multi Class\n",
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"id": "d7aa1379-5cbd-4284-8d99-373bfd02c807",
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"id": "1",
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{
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},
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"The natural representation of this multiclass is a onehot encoding accessible (and settable!) via the `labels_onehot` property."
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"If you can you can also get the labels as a ragged list of lists via the `labels` property"
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docs/examples/single-class.ipynb

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"cells": [
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"# Single Class\n"
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"```{note}\n",
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"After you label the images then the labels will be available as a list:"
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setup.cfg

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author = Ian Hunt-Isaak
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author_email = [email protected]
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license = BSD-3-Clause
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license_file = LICENSE
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license_files = LICENSE
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classifiers =
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Development Status :: 5 - Production/Stable
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Framework :: Matplotlib
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License :: OSI Approved :: BSD License
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Natural Language :: English
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Programming Language :: Python :: 3
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Programming Language :: Python :: 3 :: Only
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Programming Language :: Python :: 3.7
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Programming Language :: Python :: 3.8
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Programming Language :: Python :: 3.9
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project_urls =
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Tracker = https://github.com/ianhi/mpl-image-labeller/issues
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python_requires = >=3.9
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zip_safe = False
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[options.extras_require]

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