Use Python to interface with Tencent Cloud to implement image processing functions

Use Python to interface with Tencent Cloud to implement image processing functions

With the rapid development of the Internet, the application of images is becoming more and more widespread. The demand for image processing is also increasing. Tencent Cloud provides a wealth of image processing functions, which can identify, crop, zoom, compress and other images. This article will introduce how to use Python to interface with Tencent Cloud to implement image processing functions.

First of all, we need to prepare the Python development environment and install the relevant dependent libraries. In this article, we will use the requests library for interface requests and the PIL library for image processing. You can install it using the pip command:

pip install requests
pip install pillow

Next, we need to create a new Tencent Cloud API key on the Tencent Cloud console to gain access to the interface. On the console, enter the "API Key Management" page, click the "New Key" button to generate an API key pair, and get two values: AccessKeyId and AccessKeySecret.

Next, we need to write Python code to call the Tencent Cloud interface. First, import the required libraries:

import requests
from PIL import Image
from io import BytesIO
import hashlib
import hmac
import base64

Then, define some necessary parameters, such as the interface address of Tencent Cloud API, request method, timestamp, etc.:

secret_id = "your_secret_id"  # 替换为你的腾讯云API密钥
secret_key = "your_secret_key"  # 替换为你的腾讯云API密钥

url = "https://face.tencentcloudapi.com/"
method = "POST"
service = "face"
host = "face.tencentcloudapi.com"
region = "ap-guangzhou"
action = "DetectFace"
version = "2018-03-01"
algorithm = "TC3-HMAC-SHA256"
timestamp = int(time.time())
date = time.strftime("%Y-%m-%d", time.localtime(timestamp))

Next, we define some images processing function. Here we take image scaling as an example:

def resize_image(image, width, height):
    size=(width, height)
    image.thumbnail(size)
    return image

Then, we convert the image into a byte stream, generate a Signature and sign it:

# Load image
image = Image.open("example.jpg")

# Resize image
new_image = resize_image(image, 200, 200)

# Convert image to byte stream
byte_stream = BytesIO()
new_image.save(byte_stream, format="JPEG")
image_data = byte_stream.getvalue()

# Generate Signature
hashed_request_payload = hashlib.sha256(image_data).hexdigest()
date = time.strftime("%Y-%m-%d", time.localtime(timestamp))
credential_scope = "{}/{}/{}/tc3_request".format(date, service, "tc3_request")
canonical_request = "POST
/

content-type:application/json
host:{}

content-type;host
{}
".format(host, hashed_request_payload)
string_to_sign = "{}
{}
{}
{}".format(algorithm, timestamp, credential_scope, hashlib.sha256(canonical_request.encode("utf-8")).hexdigest())
secret_date = hmac.new(("TC3" + secret_key).encode("utf-8"), date.encode("utf-8"), hashlib.sha256).digest()
secret_service = hmac.new(secret_date, service.encode("utf-8"), hashlib.sha256).digest()
secret_signing = hmac.new(secret_service, "tc3_request".encode("utf-8"), hashlib.sha256).digest()
signature = hmac.new(secret_signing, string_to_sign.encode("utf-8"), hashlib.sha256).hexdigest()

Finally, we pass the Signature through the Authentication parameter in the request header , and send a request:

# Send request
headers = {
    "Content-Type": "application/json",
    "Host": host,
    "Authorization": "{} Credential={}/{}, SignedHeaders=content-type;host, Signature={}".format(algorithm, secret_id, credential_scope, signature)
}
params = {
    "Action": action,
    "Version": version,
    "ImageBase64": base64.b64encode(image_data).decode("utf-8"),
    "MaxFaceNum": 1
}
response = requests.post(url, headers=headers, json=params)

The above is a sample code that uses Python to connect with the Tencent Cloud interface to implement image processing functions. By calling Tencent Cloud's API interface, image processing can be easily performed. During the actual development process, you can call other image processing interfaces provided by Tencent Cloud according to your own needs to achieve richer functions.

I hope this article will help you understand the interface between Python and Tencent Cloud and realize the image processing function!

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