Python3 - Docker部署caffe open_nsfw 图片鉴黄
Posted 韩俊强
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文章目录
本篇博文重点介绍 Centos:6.9 Docker部署Caffe, 测试open_nsfw实例, 意在学习caffe的快速安装, 这里以cpu版本的caffe安装为例, 简单应用 open_nsfw 鉴黄库, 当前使用图片和视频的项目越来越多, 在此基础上, 进一步封装可以商用, 节省成本。
1. Docker部署caffe
[harry@k8s-master01 open_nsfw]$ docker pull elezar/caffe:cpu
cpu: Pulling from elezar/caffe
6c953ac5d795: Pull complete
3eed5ff20a90: Pull complete
f8419ea7c1b5: Pull complete
51900bc9e720: Pull complete
a3ed95caeb02: Pull complete
b968c02ba977: Pull complete
291f35fdb68c: Pull complete
6c428669041b: Pull complete
ee9f5a7f3403: Pull complete
380df6ccf740: Pull complete
Digest: sha256:d2fc0a3e942290fdf275cc072f329557b1ba1b0210436c42cd11481d7b4b318c
Status: Downloaded newer image for elezar/caffe:cpu
docker.io/elezar/caffe:cpu
检测caffe是否安装成功
# 查看caffe版本号
[harry@k8s-master01 open_nsfw]$ docker run -ti elezar/caffe:cpu caffe --version
libdc1394 error: Failed to initialize libdc1394
caffe version 1.0.0-rc3
# 查看caffe镜像
[harry@k8s-master01 open_nsfw]$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
elezar/caffe cpu aadc51f74429 5 years ago 1.31GB
2. 下载open_nsfw
wget https://github.com/yahoo/open_nsfw.git
3. 运行caffe
# 切换到刚才下载的open_nsfw文件夹
[harry@k8s-master01 ]$ cd open_nsfw
# 放几张待测试的图片
[harry@k8s-master01 open_nsfw]$ tree
.
├── 111.jpg
├── 222.jpg
├── 333.jpg
├── classify_nsfw.py
├── LICENSE.md
├── nsfw_model
│ ├── deploy.prototxt
│ └── resnet_50_1by2_nsfw.caffemodel
└── README.md
# 运行caffe
# --volume=$(pwd):/workspace 工作目录映射
# $(pwd)为当前文件路径
# /workspace 为caffe工作路径
[harry@k8s-master01 open_nsfw]$ docker run -ti --volume=$(pwd):/workspace elezar/caffe:cpu /bin/bash
root@c74059855431:/workspace#
4. 运行鉴黄图片
# 使用open_nsfw识别库 检测图片
root@27a3cf6c655f:/workspace# python ./classify_nsfw.py --model_def nsfw_model/deploy.prototxt --pretrained_model nsfw_model/resnet_50_1by2_nsfw.caffemodel 333.jpg
libdc1394 error: Failed to initialize libdc1394
WARNING: Logging before InitGoogleLogging() is written to STDERR
I0417 12:29:12.823567 21 net.cpp:49] Initializing net from parameters:
name: "ResNet_50_1by2_nsfw"
state
phase: TEST
layer
name: "data"
type: "Input"
top: "data"
input_param
shape
dim: 1
dim: 3
dim: 224
dim: 224
...............
...............
I0417 12:28:58.549093 20 net.cpp:219] scale_1 does not need backward computation.
I0417 12:28:58.549103 20 net.cpp:219] bn_1 does not need backward computation.
I0417 12:28:58.549154 20 net.cpp:219] conv_1 does not need backward computation.
I0417 12:28:58.549166 20 net.cpp:219] data does not need backward computation.
I0417 12:28:58.549175 20 net.cpp:261] This network produces output prob
I0417 12:28:58.549315 20 net.cpp:274] Network initialization done.
I0417 12:28:58.809204 20 net.cpp:752] Ignoring source layer loss
('NSFW score: ', 0.81271326541900635)
# 很明显0.8值高了, 你懂得~ 自己手动试试吧~
好啦🌶🌶, 关于caffe-open_nsfw鉴黄就介绍到这里, 喜欢点个赞吧~ ❤☕️
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