Image classification models for Keras
Project description
Large-scale image classification networks
Collection of large-scale image classification models on Keras (with MXNet backend), pretrained on the ImageNet-1k dataset.
Installation
To install, use:
pip install kerascv mxnet>=1.2.1
To enable different hardware supports such as GPUs, check out MXNet variants. For example, you can install with CUDA-9.2 supported MXNet:
pip install kerascv mxnet-cu92>=1.2.1
After installation change the value of the field image_data_format
to channels_first
in the file ~/.keras/keras.json
.
Usage
Example of using the pretrained ResNet-18 model:
from kerascv.model_provider import get_model as kecv_get_model
net = kecv_get_model("resnet18", pretrained=True)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
kerascv-0.0.13.tar.gz
(34.7 kB
view hashes)
Built Distribution
Close
Hashes for kerascv-0.0.13-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fd837b9b34b2ab1b98520c67c67e9afdd5c6f8ef33515416727b524346e287ef |
|
MD5 | d6aa5623e948d30ce8f3e7e974a310aa |
|
BLAKE2b-256 | b15335926d4202f6d10fb2152b67c63b213232c4e26ee1c845a7c6c3de62a075 |