# nsfw

**Repository Path**: tib/nsfw

## Basic Information

- **Project Name**: nsfw
- **Description**: 黄图鉴别工具 写在前面：不要找我要训练数据，我是遵纪守法的好公民，训练数据已经删除
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 12
- **Created**: 2019-01-23
- **Last Updated**: 2022-08-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# NSFW Model

This repo contains code for running Not Suitable for Work (NSFW) classification.

[online demo](http://ai.midday.me/)

## Usage

#### script 

```bash
python nsfw_predict.py /tmp/test/test.jpeg
```

result : 
```bash
{'class': 'sexy', 'probability': {'drawings': 0.008320281, 'hentai': 0.0011919827, 'neutral': 0.13077603, 'porn': 0.13146976, 'sexy': 0.72824186}}
```

can find the meaning of every label at repo [nsfw_data_scrapper](https://github.com/alexkimxyz/nsfw_data_scrapper)

#### Deploy by TensorFlow Serving

your have to install [Tensorflow Serving](https://www.tensorflow.org/serving/) first

start the server
```bash
./start_tensorflow_serving.sh
```

test server
```bash
python serving_client.py /tmp/test/test.jpeg
```


## Train

train code at [resnet](./resnet)

train a new model

1. convert source to tfrecord user ```convert_image_to_tfrecord.py```
2. train a model from scratch or fine tune

the model code copy from [Tensorflow offical model](https://github.com/tensorflow/models/tree/master/official/resnet)


## Data

you can find the detail at repo [nsfw_data_scrapper](https://github.com/alexkimxyz/nsfw_data_scrapper)