tutorials | ImageJ2 programming examples

by imagej Jupyter Notebook Version: Current License: Unlicense

X-Ray Key Features Code Snippets(3)Community Discussions Vulnerabilities Install Support

kandi X-RAY | tutorials Summary

tutorials is a Jupyter Notebook library. tutorials has no bugs, it has a Permissive License and it has low support. However tutorials has 1 vulnerabilities. You can download it from GitHub.

This project contains example code for working with ImageJ and SciJava.

Support

Quality

Security

License

Reuse

Support

tutorials has a low active ecosystem.

It has 145 star(s) with 106 fork(s). There are 40 watchers for this library.

It had no major release in the last 6 months.

There are 24 open issues and 27 have been closed. On average issues are closed in 281 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tutorials is current.

Quality

tutorials has no bugs reported.

Security

tutorials has 1 vulnerability issues reported (0 critical, 1 high, 0 medium, 0 low).

License

tutorials is licensed under the Unlicense License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

tutorials releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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tutorials Key Features

No Key Features are available at this moment for tutorials.

tutorials Examples and Code Snippets

Create a csv dataset from a csv file .

python

Lines of Code : 296

License : Non-SPDX (Apache License 2.0)

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def make_csv_dataset_v2(
    file_pattern,
    batch_size,
    column_names=None,
    column_defaults=None,
    label_name=None,
    select_columns=None,
    field_delim=",",
    use_quote_delim=True,
    na_value="",
    header=True,
    num_epochs=

Distribute the dataset .

python

Lines of Code : 120

License : Non-SPDX (Apache License 2.0)

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def experimental_distribute_dataset(self, dataset, options=None):
    # pylint: disable=line-too-long
    """Creates `tf.distribute.DistributedDataset` from `tf.data.Dataset`.

    The returned `tf.distribute.DistributedDataset` can be iterated over

Returns a scoped scope .

python

Lines of Code : 93

License : Non-SPDX (Apache License 2.0)

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def scope(self):
    """Context manager to make the strategy current and distribute variables.

    This method returns a context manager, and is used as follows:

    >>> strategy = tf.distribute.MirroredStrategy(["GPU:0", "GPU:1"])
    >

Community Discussions

No Community Discussions are available at this moment for tutorials.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tutorials

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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