Difference between r1.5 and the current
@@ -1,3 +1,6 @@
[머신러닝스터디/2016]
[머신러닝스터디/2016/목차]
== 내용 ==
* transfer, image retraining, fine-tune* 튜토리얼로 [https://www.tensorflow.org/versions/r0.9/how_tos/image_retraining/index.html#training-on-flowers flower classification]을 해 보자.
* bazel build는 까다롭다.
@@ -14,5 +17,6 @@
* docker
== 더보기 ==
== 더보기 ==
* https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim
* https://github.com/tensorflow/models/blob/master/slim/scripts/finetune_inception_v1_on_flowers.sh
* install bazel in linux: [https://www.bazel.io/versions/master/docs/install.html#ubuntu link]
* tensorflow model slim: [https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim link]
* flower classification tutorial script : [https://github.com/tensorflow/models/blob/master/slim/scripts/finetune_inception_v1_on_flowers.sh link]
내용 ¶
- transfer, image retraining, fine-tune
- 튜토리얼로 flower classification을 해 보자.
- bazel build는 까다롭다.
- tensorflow 0.10rc에서 예제 스크립트 실행 불가
- tensorflow 0.11.0rc설치 후 실행 가능
- 바이너리 링크 참고: https://github.com/tensorflow/tensorflow/blob/r0.11/tensorflow/g3doc/get_started/os_setup.md
# Ubuntu/Linux 64-bit, CPU only, Python 2.7 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit $ sudo apt-get install python-pip python-dev python-virtualenv
- bazel build는 까다롭다.
- docker
