Viewing file:  resnext.py (1020 B) -rw-r--r--
Select action/file-type:
 (+) |  (+) |  (+) | Code (+) | Session (+) |  (+) | SDB (+) |  (+) |  (+) |  (+) |  (+) |  (+) |
"""ResNeXt models for Keras.
# Reference paper
- [Aggregated Residual Transformations for Deep Neural Networks]
(https://arxiv.org/abs/1611.05431) (CVPR 2017)
# Reference implementations
- [TensorNets]
(https://github.com/taehoonlee/tensornets/blob/master/tensornets/resnets.py)
- [Torch ResNeXt]
(https://github.com/facebookresearch/ResNeXt/blob/master/models/resnext.lua)
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from . import imagenet_utils
from .imagenet_utils import decode_predictions
from .resnet_common import ResNeXt50
from .resnet_common import ResNeXt101
def preprocess_input(x, **kwargs):
"""Preprocesses a numpy array encoding a batch of images.
# Arguments
x: a 4D numpy array consists of RGB values within [0, 255].
data_format: data format of the image tensor.
# Returns
Preprocessed array.
"""
return imagenet_utils.preprocess_input(x, mode='torch', **kwargs)
|