cloud-volume | Read and write Neuroglancer datasets
kandi X-RAY | cloud-volume Summary
kandi X-RAY | cloud-volume Summary
cloud-volume is a Python library. cloud-volume has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install cloud-volume' or download it from GitHub, PyPI.
Read and write Neuroglancer datasets programmatically.
Read and write Neuroglancer datasets programmatically.
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Quality
Security
License
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Support
cloud-volume has a low active ecosystem.
It has 113 star(s) with 39 fork(s). There are 27 watchers for this library.
There were 7 major release(s) in the last 12 months.
There are 78 open issues and 203 have been closed. On average issues are closed in 26 days. There are 2 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of cloud-volume is 8.33.0
Quality
cloud-volume has 0 bugs and 0 code smells.
Security
cloud-volume has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
cloud-volume code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
cloud-volume is licensed under the BSD-3-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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cloud-volume releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
cloud-volume saves you 3278 person hours of effort in developing the same functionality from scratch.
It has 14633 lines of code, 1152 functions and 82 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed cloud-volume and discovered the below as its top functions. This is intended to give you an instant insight into cloud-volume implemented functionality, and help decide if they suit your requirements.
- Return a set of unique segments
- Retrieve the leaves of a segment
- Get the leaves for a given root id
- Create a bounding box from an object
- Transfer files to cloudpath
- Display error message
- Create a new dataset
- Wrapper for strict extract
- Fetch info about the experiment
- Generate a hash of a key
- Benchmark a given volume
- Upload an image
- Get the mesh data
- Get mesh data
- Construct a Skeleton from a string
- Create a Graphene
- Create image info
- Download files from bounding box
- Child upload process
- Get the mappings for a chunk
- Check if the info file is valid
- Save an array to cloudvolume
- Get a list of meshes
- Create a precomputed cloud
- Create a viewer for the skeleton
- Download files from bbox
Get all kandi verified functions for this library.
cloud-volume Key Features
No Key Features are available at this moment for cloud-volume.
cloud-volume Examples and Code Snippets
No Code Snippets are available at this moment for cloud-volume.
Community Discussions
No Community Discussions are available at this moment for cloud-volume.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install cloud-volume
Cloud-volume is regularly tested on Ubuntu with 3.6, 3.7, 3.8, and 3.9. We officially support Linux and Mac OS. Windows is community supported. After installation, you'll also need to set up your cloud credentials if you're planning on writing files or reading from a private dataset. Once you're finished setting up, you can try reading from a public dataset.
Support
We currently support reading the sharded skeleton format within Precomputed that is used in some newer datasets. Other data types are forthcoming.
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