Pre-release
This release is a pre-release and may not be stable for production use.
GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in computer vision.
It is designed for engineers, researchers, and students to fast prototype products and research ideas based on these models.
Installation
To install, use:
To enable different hardware supports such as GPUs, check out mxnet variants.
For example, you can install cuda-9.0 supported mxnet alongside gluoncv:
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Metadata
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Release files for gluoncv 0.2.0b20180502
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gluoncv-0.2.0b20180502.tar.gz | 67.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gluoncv-0.2.0b20180502-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 158.1 kB
Release files / gluoncv-0.2.0b20180502.tar.gz
| Download URL | gluoncv-0.2.0b20180502.tar.gz |
|---|---|
| Size | 67.3 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / gluoncv-0.2.0b20180502-py2.py3-none-any.whl
| Download URL | gluoncv-0.2.0b20180502-py2.py3-none-any.whl |
|---|---|
| Size | 90.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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