Turn Images into Sketches with Alibaba Cloud Serverless Functions

Scenario Introduction

The article demonstrates how to deploy a simple Python function on Alibaba Cloud Serverless Function Compute that converts ordinary photos into sketch‑style images. Uploaded pictures in a designated OSS bucket are processed automatically and the resulting sketches are saved to a separate OSS bucket.

Related Concepts

Serverless (Serverless computing) abstracts away server management, allowing developers to focus on business logic. Function Compute (FC) is Alibaba Cloud’s FaaS offering, often combined with BaaS services such as OSS, SLS, and RDS to build complete applications.

Prerequisites

Alibaba Cloud account with Function Compute, OSS, and SLS services enabled.

Python code that converts a normal image to a sketch (uses OpenCV).

Test images ready for upload.

Two OSS buckets: one for input images (e.g., sketch-image-input) and one for output sketches (e.g., sketch-image-output). The output bucket must be different to avoid infinite trigger loops.

Step 1: Create a Function Compute Service

In the Alibaba Cloud console, select Function Compute and click “Create Service”. Provide a service name and description.

Enter the service, then click “Create Function”. Choose Python 3.6 as the runtime, select “Upload code” and use the sample code template. Set the handler to process event requests.

Configure the trigger: choose OSS, select the input bucket ( sketch-image-input), and filter for .jpg files to avoid unintended triggers.

Step 2: Implement the Sketch Function

Write the Python script that reads an image, applies OpenCV operations to produce a sketch, and saves the result.

# -*- coding: utf-8 -*-
import cv2
import json
import logging
import oss2

def sketch_image(source_image, target_image):
    # read image
    image = cv2.imread(source_image)
    # sketch image
    grey_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    invert_image = cv2.bitwise_not(grey_image)
    gaussian_blur_image = cv2.GaussianBlur(invert_image, (7, 7), 0)
    inverse_image = cv2.bitwise_not(gaussian_blur_image)
    sketch_image_result = cv2.divide(grey_image, inverse_image, scale=256.0)
    # save image
    cv2.imwrite(target_image, sketch_image_result)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

def handler(event, context):
    logger = logging.getLogger()
    evt = json.loads(event)
    creds = context.credentials
    # Required by OSS SDK
    auth = oss2.StsAuth(creds.access_key_id, creds.access_key_secret, creds.security_token)
    evt = evt['events'][0]
    bucket_name = evt['oss']['bucket']['name']
    endpoint = 'oss-' + evt['region'] + '.aliyuncs.com'
    bucket_input = oss2.Bucket(auth, endpoint, bucket_name)
    bucket_output = oss2.Bucket(auth, endpoint, 'sketch-image-output')
    logger.info('oss endpoint: %s' % endpoint)
    objectName = evt['oss']['object']['key']
    logger.info('oss objectName: %s' % objectName)
    newKey = 'sketch_' + objectName
    # Download image
    source_image = '/tmp/%s' % objectName
    bucket_input.get_object_to_file(objectName, source_image)
    logger.info('download image %s success.' % source_image)
    # Sketch image
    target_image = '/tmp/%s' % newKey
    sketch_image(source_image, target_image)
    # Upload image
    with open(target_image, 'rb') as fileobj:
        bucket_output.put_object(newKey, fileobj)
    logger.info('upload image %s success.' % newKey)

Step 3: Deploy and Test

After uploading the function code, enable SLS logging for easier debugging. Upload a test JPEG to the input bucket; the function will be triggered, process the image, and place the sketch in the output bucket.

Verify the result by browsing the output bucket; the sketch images appear as expected.

Batch uploading multiple photos confirms that the function handles concurrent triggers reliably.

References

• Alibaba Cloud FC OSS trigger SDK: https://help.aliyun.com/document_detail/74765.html

• OSS file download/upload SDK: https://help.aliyun.com/document_detail/88426.html

• FC Python built‑in modules: https://help.aliyun.com/document_detail/158208.html