CoreMLModel

CoreML创建自己的.mlmodel的心酸历程，足足摆弄了半天，各种坑。

[Permission denied]问题

• pip install -U coremltools

• 从图也可以看出coremltools包含numpy,six,protobuf,coremltools。 因为权限问题导致失败

• sudo pip install -U coremltools
• 遇到[Permission denied]都要加sudo

ImportError: No module named pkg_resources 问题

• Step: 1 Login in root user.

sudo su root

• Step: 2 Uninstall python-pip package if existing.

apt-get purge -y python-pip

• Step: 3 Download files using wget command(File download in pwd )

wget https://bootstrap.pypa.io/get-pip.py

• Step: 4 Run python file.

python ./get-pip.py

• Step: 5 Finaly exicute installation command.

apt-get install python-pip

Note: User must be root.

好吧，这两个问题遍布整个流程，期间各种小问题我已经不记得了，接下来就开始正文了

1. 下载coremltools

sudo pip install -U coremltools

2. 下载pip.py文件

sudo python get-pip.py

3. 下载scikit-learn

sudo pip install -U numpy scipy scikit-learn

4. 下载panda

sudo pip install pandas

准备就绪，开工

创建csv文件

1. csv文件属性Square_Feet，Price
2. 记录文件所存储位置，调用的时候需要

在终端输入生成.mlmodel文件

1. 导入需要的类
2. 调用csv文件
3. coremltools转换成.mlmodel文件
4. author,license,description描述
5. 输入Square_Feet，输出Price，保存

• import coremltools

• from sklearn.linear_model import LinearRegression

• import pandas as pd

• load data

• data = pd.read_csv('/Users/sansi/Desktop/CoreMLModel/input_data.csv')

• train a model

• model = LinearRegression()

• model.fit(data[["Square_Feet"]], data["Price"])

• convert and save the scikit-learn model

• coreml_model = coremltools.converters.sklearn.convert(model, "Square_Feet", "Price")

• set model metadata

• coreml_model.author = 'tongle'

• coreml_model.license = 'BSD'

• coreml_model.short_description = 'Predicts the price of a house in the Seattle area.'

• set feature descriptions manually

• coreml_model.input_description['Square_Feet'] = 'Size (in square feet)'

• set the output descriptions

• coreml_model.output_description['Price'] = 'Price of the house'

• save the mdel

• coreml_model.save('HousePricer.mlmodel')

如果没有一点python功底，我都要死在电脑前了，哈哈