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In-depth study of Golang and Baidu AI interface: Mastering image analysis technology
Introduction:
With the development of artificial intelligence, image analysis technology has been widely used in various fields Applications are becoming more and more widespread, and Baidu AI interface provides a powerful set of image recognition and analysis tools. This article will introduce how to implement the application of image analysis technology by using the Golang programming language and Baidu AI interface. By reading this article, you will understand how to use the Golang programming language to call Baidu AI interface to implement image analysis functions, and learn about some commonly used image processing technologies and algorithms.
1. Preparation work
Before we start, we need to do some preparation work. First, we need to have a Baidu AI account, register on the official website and create an application, and then obtain the corresponding API Key and Secret Key. Secondly, we need to build a Golang development environment locally and install some necessary libraries for development.
2. Install dependent libraries
Before we start writing code, we need to install some necessary libraries to communicate with Baidu AI interface. We can use the following command to install these libraries:
go get github.com/go-resty/resty/v2 go get github.com/levigross/grequests
The above two libraries are used to make HTTP requests and process JSON data respectively.
3. Call Baidu AI interface
package main import ( "fmt" "github.com/go-resty/resty/v2" ) func main() { apiKey := "your_api_key" secretKey := "your_secret_key" imageURL := "https://example.com/image.jpg" client := resty.New() resp, err := client.R(). SetFormData(map[string]string{ "image": imageURL, "api_key": apiKey, "api_sign": secretKey, }). Post("https://aip.baidubce.com/rest/2.0/image-classify/v2/advanced_general") if err != nil { fmt.Println("Error:", err) return } fmt.Println("Response:", resp.String()) }
In this code, we first define the API Key and Secret Key of the Baidu AI interface, and then set the URL of the image to be recognized. Next, we created an HTTP client using the go-resty/resty
library and sent a POST request to the Baidu AI interface. The requested content includes image URL, API Key and Secret Key. Finally, we print out the results returned by the interface.
package main import ( "fmt" "github.com/go-resty/resty/v2" ) func main() { apiKey := "your_api_key" secretKey := "your_secret_key" imageURL := "https://example.com/image.jpg" client := resty.New() resp, err := client.R(). SetFormData(map[string]string{ "image": imageURL, "api_key": apiKey, "api_sign": secretKey, }). Post("https://aip.baidubce.com/rest/2.0/face/v3/detect") if err != nil { fmt.Println("Error:", err) return } fmt.Println("Response:", resp.String()) }
In this code, we send a POST request to Baidu AI interface. The requested content includes image URL, API Key and Secret Key. The results returned by the interface include information related to face recognition and appearance rating.
4. Summary
Through the introduction of this article, we have learned how to use the Golang programming language and Baidu AI interface to implement the application of image analysis technology. We learned how to call Baidu AI interface for image recognition and image analysis, and demonstrated the specific calling process through sample code. I hope that sharing this article can help readers who want to learn more about Golang and image analysis technology.
Source of code examples: https://github.com/BingquanChen/golang-baidu-ai-examples
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