


Tutorial: Python connects to Huawei Cloud interface to implement image style migration and conversion functions
Tutorial: Python connects to Huawei Cloud interface to implement image style migration and conversion functions
Introduction:
With the development of artificial intelligence, image style migration and conversion have become a popular research direction in the field of computer vision one. Huawei Cloud provides powerful image processing capabilities based on deep learning technology. This tutorial will introduce how to use Python to connect to the Huawei Cloud interface to implement image style migration and conversion.
- Register a Huawei Cloud account
First, we need to register an account on the Huawei Cloud official website and create a project. After logging in to the Huawei Cloud console, select the region and project in the upper left corner, and then click the "Create Project" button. - Create an IAM user and obtain AK/SK
In order to use Huawei Cloud related services, we need to create an IAM user and obtain its Access Key (AK) and Secret Key (SK).
Select "User Management" - "IAM User Management" in the menu bar of the console, and then click "New User". Set a user name, select "Automatically generate" Access Key and Secret Key, and associate the corresponding policy with the user.
Write down the AK and SK obtained, which will be used to connect to the Huawei Cloud interface.
- Install Python SDK
Next, we need to install Huawei Cloud’s Python SDK. Execute the following command in the command line:
pip install huaweicloud-sdk-python
After the installation is complete, you can use Huawei Cloud functions in Python code.
- Connecting to Huawei Cloud Interface
First, we need to introduce the relevant modules of Huawei Cloud SDK and the common libraries of Python:
from huaweicloud_sdk.core.auth.credentials import BasicCredentials from huaweicloud_sdk.imagerec.v1.region import Region from huaweicloud_sdk.imagerec.v1.client import ImageRecClient import matplotlib.pyplot as plt import numpy as np import requests from PIL import Image
In the following code , we will use the image style migration and conversion function provided by Huawei Cloud.
# 创建华为云的认证对象 credentials = BasicCredentials(access_key='<your-access-key>', secret_key='<your-secret-key>') # 创建华为云图像风格迁移与转换客户端 client = ImageRecClient.new_builder() .with_region(Region.CN_NORTH_4) .with_credentials(credentials) .build() # 读取本地图像文件 content_image = Image.open('<path-to-content-image>') style_image = Image.open('<path-to-style-image>') # 将图像转换为numpy数组 content_image_np = np.array(content_image) style_image_np = np.array(style_image) # 发送图像风格迁移与转换请求 result = client.artistic_style_transfer(content_image_np, style_image_np, 0.5) # 显示风格迁移后的图像 transfer_image = Image.fromarray(result) plt.imshow(transfer_image) plt.axis('off') plt.show()
In the above code, you need to replace access_key
and secret_key
with your own AK and SK, and specify the content image and style image to be style migrated path.
- Run the program
Save the above code as a Python file (such as style_transfer.py), and execute the following command on the command line to run the program:
python style_transfer.py
Program It will automatically connect to the Huawei Cloud interface, send the content image and style image to Huawei Cloud, and return the style-migrated image. Finally, the program displays the resulting image after style transfer.
Conclusion:
This tutorial introduces how to use Python to connect to the Huawei Cloud interface to implement image style migration and conversion. Through the powerful computing capabilities of Huawei Cloud, we can easily implement image style migration, bringing more possibilities to image processing tasks. We hope that through this tutorial, readers can make better use of Huawei Cloud services and improve image processing effects.
The above is the detailed content of Tutorial: Python connects to Huawei Cloud interface to implement image style migration and conversion functions. For more information, please follow other related articles on the PHP Chinese website!

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