Viewing file:  resnet.py (1.02 KB) -rw-r--r--
Select action/file-type:
 (+) |  (+) |  (+) | Code (+) | Session (+) |  (+) | SDB (+) |  (+) |  (+) |  (+) |  (+) |  (+) |
"""ResNet models for Keras.
# Reference paper
- [Deep Residual Learning for Image Recognition]
(https://arxiv.org/abs/1512.03385) (CVPR 2016 Best Paper Award)
# Reference implementations
- [TensorNets]
(https://github.com/taehoonlee/tensornets/blob/master/tensornets/resnets.py)
- [Caffe ResNet]
(https://github.com/KaimingHe/deep-residual-networks/tree/master/prototxt)
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from . import imagenet_utils
from .imagenet_utils import decode_predictions
from .resnet_common import ResNet50
from .resnet_common import ResNet101
from .resnet_common import ResNet152
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='caffe', **kwargs)
|