Metadata-Version: 2.0
Name: cloud-volume
Version: 0.2.0
Summary: Read and write neuroglancer Precomputed formats to cloud storage
Home-page: https://github.com/seung-lab/cloud-volume/
Author: Ignacio Tartavull, William Silversmith, and others
Author-email: ws9@princeton.edu
License: BSD
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Utilities
Requires-Dist: Pillow (==4.2.1)
Requires-Dist: backports-abc (==0.5)
Requires-Dist: boto3 (==1.4.7)
Requires-Dist: chardet (==3.0.4)
Requires-Dist: google-auth (==1.0.2)
Requires-Dist: google-cloud (==0.27)
Requires-Dist: intern (==0.9.4)
Requires-Dist: jsonschema (==2.6.0)
Requires-Dist: numpy (==1.13.1)
Requires-Dist: protobuf (==3.3.0)
Requires-Dist: pytest (==3.0.7)
Requires-Dist: python-jsonschema-objects (==0.2.1)
Requires-Dist: requests (==2.18.4)
Requires-Dist: six (==1.10.0)
Requires-Dist: tenacity (==4.4.0)
Requires-Dist: tqdm (==4.7.6)
Requires-Dist: urllib3[secure]

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# cloud-volume

Python client for reading and writing to Neuroglancer Precomputed volumes on cloud services. (https://github.com/google/neuroglancer/tree/master/src/neuroglancer/datasource/precomputed)

When working with a particular dataset, say an EM scan of a mouse, fish, or fly brain, you'll typically store that as a grayscale data layer accessible to neuroglanger. You may store additional labellings and processing results as other layers.


## Usage

Supports reading and writing to neuroglancer data layers on Amazon S3, Google Storage, and the local file system.

Supported URLs are of the forms:

$PROTOCOL://$BUCKET/$DATASET/$LAYER  

### Supported Protocols 
* gs:   Google Storage
* s3:   Amazon S3
* boss: The BOSS (https://docs.theboss.io/docs)
* file: Local File System (absolute path)

### Examples

```
vol = CloudVolume('gs://mybucket/retina/image') # Basic Example
image = vol[:,:,:] # Download the entire image stack into a numpy array
vol[64:128, 64:128, 64:128] = image # Write a 64^3 image to the volume
vol.save_mesh(12345) # save 12345 as ./12345.obj
vol.save_mesh([12345, 12346, 12347]) # merge three segments into one obj
```

## Setup

You'll need to set up your cloud credentials as well as the main install.

### Credentials

```
mkdir -p ~/.neuroglancer/secrets/
echo $GOOGLE_STORAGE_PROJECT > ~/.neuroglancer/project_name # needed for Google
mv aws-secret.json ~/.neuroglancer/secrets/ # needed for Google
mv google-secret.json ~/.neuroglancer/secrets/ # needed for Amazon
```

### pip

```
pip install cloud-volume
```

### Manual
```
git clone git@github.com:seung-lab/cloud-volume.git
cd cloud-volume
mkvirtualenv cloud-volume
workon cloud-volume
pip install -e .
```

## Other Languages

Julia - https://github.com/seung-lab/CloudVolume.jl



