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https://github.com/paulfitz/keras_cli
keras cli
https://github.com/paulfitz/keras_cli
cli command-line keras
Last synced: 5 days ago
JSON representation
keras cli
- Host: GitHub
- URL: https://github.com/paulfitz/keras_cli
- Owner: paulfitz
- Created: 2017-03-03T20:13:32.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-03-03T20:30:00.000Z (over 7 years ago)
- Last Synced: 2024-10-11T07:43:19.296Z (28 days ago)
- Topics: cli, command-line, keras
- Language: Python
- Size: 1.95 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Very unofficial keras cli
=========================
[keras](https://github.com/fchollet/keras/) is great but it could do with a cli maybe?
I've started sticking some stuff I repeatedly write small scripts for here.
```
usage: keras [-h] [--custom CUSTOM] filename
positional arguments:
filename model to use
optional arguments:
-h, --help show this help message and exit
--custom CUSTOM custom objects to load (loss functions etc)
```
Install
-------
```
pip install keras_cli
```
Example
-------
```
$ keras yolo9000.h5
____________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
====================================================================================================
input_1 (InputLayer) (None, 416, 416, 3) 0
____________________________________________________________________________________________________
convolution2d_1 (Convolution2D) (None, 416, 416, 32) 864 input_1[0][0]
____________________________________________________________________________________________________
batchnormalization_1 (BatchNorma (None, 416, 416, 32) 128 convolution2d_1[0][0]
____________________________________________________________________________________________________
leakyrelu_1 (LeakyReLU) (None, 416, 416, 32) 0 batchnormalization_1[0][0]
____________________________________________________________________________________________________
maxpooling2d_1 (MaxPooling2D) (None, 208, 208, 32) 0 leakyrelu_1[0][0]
____________________________________________________________________________________________________
convolution2d_2 (Convolution2D) (None, 208, 208, 64) 18432 maxpooling2d_1[0][0]
____________________________________________________________________________________________________
batchnormalization_2 (BatchNorma (None, 208, 208, 64) 256 convolution2d_2[0][0]
____________________________________________________________________________________________________
leakyrelu_2 (LeakyReLU) (None, 208, 208, 64) 0 batchnormalization_2[0][0]
____________________________________________________________________________________________________
maxpooling2d_2 (MaxPooling2D) (None, 104, 104, 64) 0 leakyrelu_2[0][0]
____________________________________________________________________________________________________
convolution2d_3 (Convolution2D) (None, 104, 104, 128) 73728 maxpooling2d_2[0][0]
____________________________________________________________________________________________________
batchnormalization_3 (BatchNorma (None, 104, 104, 128) 512 convolution2d_3[0][0]
____________________________________________________________________________________________________
leakyrelu_3 (LeakyReLU) (None, 104, 104, 128) 0 batchnormalization_3[0][0]
____________________________________________________________________________________________________
convolution2d_4 (Convolution2D) (None, 104, 104, 64) 8192 leakyrelu_3[0][0]
____________________________________________________________________________________________________
batchnormalization_4 (BatchNorma (None, 104, 104, 64) 256 convolution2d_4[0][0]
____________________________________________________________________________________________________
leakyrelu_4 (LeakyReLU) (None, 104, 104, 64) 0 batchnormalization_4[0][0]
____________________________________________________________________________________________________
convolution2d_5 (Convolution2D) (None, 104, 104, 128) 73728 leakyrelu_4[0][0]
____________________________________________________________________________________________________
batchnormalization_5 (BatchNorma (None, 104, 104, 128) 512 convolution2d_5[0][0]
____________________________________________________________________________________________________
leakyrelu_5 (LeakyReLU) (None, 104, 104, 128) 0 batchnormalization_5[0][0]
____________________________________________________________________________________________________
maxpooling2d_3 (MaxPooling2D) (None, 52, 52, 128) 0 leakyrelu_5[0][0]
____________________________________________________________________________________________________
convolution2d_6 (Convolution2D) (None, 52, 52, 256) 294912 maxpooling2d_3[0][0]
____________________________________________________________________________________________________
batchnormalization_6 (BatchNorma (None, 52, 52, 256) 1024 convolution2d_6[0][0]
____________________________________________________________________________________________________
leakyrelu_6 (LeakyReLU) (None, 52, 52, 256) 0 batchnormalization_6[0][0]
____________________________________________________________________________________________________
convolution2d_7 (Convolution2D) (None, 52, 52, 128) 32768 leakyrelu_6[0][0]
____________________________________________________________________________________________________
batchnormalization_7 (BatchNorma (None, 52, 52, 128) 512 convolution2d_7[0][0]
____________________________________________________________________________________________________
leakyrelu_7 (LeakyReLU) (None, 52, 52, 128) 0 batchnormalization_7[0][0]
____________________________________________________________________________________________________
convolution2d_8 (Convolution2D) (None, 52, 52, 256) 294912 leakyrelu_7[0][0]
____________________________________________________________________________________________________
batchnormalization_8 (BatchNorma (None, 52, 52, 256) 1024 convolution2d_8[0][0]
____________________________________________________________________________________________________
leakyrelu_8 (LeakyReLU) (None, 52, 52, 256) 0 batchnormalization_8[0][0]
____________________________________________________________________________________________________
maxpooling2d_4 (MaxPooling2D) (None, 26, 26, 256) 0 leakyrelu_8[0][0]
____________________________________________________________________________________________________
convolution2d_9 (Convolution2D) (None, 26, 26, 512) 1179648 maxpooling2d_4[0][0]
____________________________________________________________________________________________________
batchnormalization_9 (BatchNorma (None, 26, 26, 512) 2048 convolution2d_9[0][0]
____________________________________________________________________________________________________
leakyrelu_9 (LeakyReLU) (None, 26, 26, 512) 0 batchnormalization_9[0][0]
____________________________________________________________________________________________________
convolution2d_10 (Convolution2D) (None, 26, 26, 256) 131072 leakyrelu_9[0][0]
____________________________________________________________________________________________________
batchnormalization_10 (BatchNorm (None, 26, 26, 256) 1024 convolution2d_10[0][0]
____________________________________________________________________________________________________
leakyrelu_10 (LeakyReLU) (None, 26, 26, 256) 0 batchnormalization_10[0][0]
____________________________________________________________________________________________________
convolution2d_11 (Convolution2D) (None, 26, 26, 512) 1179648 leakyrelu_10[0][0]
____________________________________________________________________________________________________
batchnormalization_11 (BatchNorm (None, 26, 26, 512) 2048 convolution2d_11[0][0]
____________________________________________________________________________________________________
leakyrelu_11 (LeakyReLU) (None, 26, 26, 512) 0 batchnormalization_11[0][0]
____________________________________________________________________________________________________
convolution2d_12 (Convolution2D) (None, 26, 26, 256) 131072 leakyrelu_11[0][0]
____________________________________________________________________________________________________
batchnormalization_12 (BatchNorm (None, 26, 26, 256) 1024 convolution2d_12[0][0]
____________________________________________________________________________________________________
leakyrelu_12 (LeakyReLU) (None, 26, 26, 256) 0 batchnormalization_12[0][0]
____________________________________________________________________________________________________
convolution2d_13 (Convolution2D) (None, 26, 26, 512) 1179648 leakyrelu_12[0][0]
____________________________________________________________________________________________________
batchnormalization_13 (BatchNorm (None, 26, 26, 512) 2048 convolution2d_13[0][0]
____________________________________________________________________________________________________
leakyrelu_13 (LeakyReLU) (None, 26, 26, 512) 0 batchnormalization_13[0][0]
____________________________________________________________________________________________________
maxpooling2d_5 (MaxPooling2D) (None, 13, 13, 512) 0 leakyrelu_13[0][0]
____________________________________________________________________________________________________
convolution2d_14 (Convolution2D) (None, 13, 13, 1024) 4718592 maxpooling2d_5[0][0]
____________________________________________________________________________________________________
batchnormalization_14 (BatchNorm (None, 13, 13, 1024) 4096 convolution2d_14[0][0]
____________________________________________________________________________________________________
leakyrelu_14 (LeakyReLU) (None, 13, 13, 1024) 0 batchnormalization_14[0][0]
____________________________________________________________________________________________________
convolution2d_15 (Convolution2D) (None, 13, 13, 512) 524288 leakyrelu_14[0][0]
____________________________________________________________________________________________________
batchnormalization_15 (BatchNorm (None, 13, 13, 512) 2048 convolution2d_15[0][0]
____________________________________________________________________________________________________
leakyrelu_15 (LeakyReLU) (None, 13, 13, 512) 0 batchnormalization_15[0][0]
____________________________________________________________________________________________________
convolution2d_16 (Convolution2D) (None, 13, 13, 1024) 4718592 leakyrelu_15[0][0]
____________________________________________________________________________________________________
batchnormalization_16 (BatchNorm (None, 13, 13, 1024) 4096 convolution2d_16[0][0]
____________________________________________________________________________________________________
leakyrelu_16 (LeakyReLU) (None, 13, 13, 1024) 0 batchnormalization_16[0][0]
____________________________________________________________________________________________________
convolution2d_17 (Convolution2D) (None, 13, 13, 512) 524288 leakyrelu_16[0][0]
____________________________________________________________________________________________________
batchnormalization_17 (BatchNorm (None, 13, 13, 512) 2048 convolution2d_17[0][0]
____________________________________________________________________________________________________
leakyrelu_17 (LeakyReLU) (None, 13, 13, 512) 0 batchnormalization_17[0][0]
____________________________________________________________________________________________________
convolution2d_18 (Convolution2D) (None, 13, 13, 1024) 4718592 leakyrelu_17[0][0]
____________________________________________________________________________________________________
batchnormalization_18 (BatchNorm (None, 13, 13, 1024) 4096 convolution2d_18[0][0]
____________________________________________________________________________________________________
leakyrelu_18 (LeakyReLU) (None, 13, 13, 1024) 0 batchnormalization_18[0][0]
____________________________________________________________________________________________________
convolution2d_19 (Convolution2D) (None, 13, 13, 28269) 28975725 leakyrelu_18[0][0]
====================================================================================================
Total params: 48,807,501
Trainable params: 48,793,101
Non-trainable params: 14,400
____________________________________________________________________________________________________
```