forked from keras-team/keras-applications
-
Notifications
You must be signed in to change notification settings - Fork 0
/
resnet.py
37 lines (27 loc) · 1.02 KB
/
resnet.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
"""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)