RGB finding in Appium via image crop

In mobile automation testing, precise element identification and validation are important to ensure the quality of our app. Appium is one of the most popular open-source automation tools for mobile applications, which offers numerous functionalities for effective software testing. It is one of the most unique and useful techniques that involve RGB by finding using image cropping. This case study will help to explore how RGB can be used in Appium to identify, detect, and verify image regions in mobile application testing. Automaton testing for mobile applications is done by finding specific RGB color values within a cropped image area using Appium, to leverage the capability to capture screenshots from the device.

About Our Client

Our client is a leading eCommerce platform dedicated to providing a wide range of high-quality products for pets and pet owners. The online store offers an extensive collection of essentials for your pet that includes food, toys, grooming supplies, health products, and accessories for dogs, cats, and small animals. With the mission to enhance the lives of the pets and their owners.

Challenge

 We were tasked with the process of verifying the display of product images in e-commerce applications, but there were no attributes or XPath to identify whether a product had an image or not. To address this, we used an RGB validation technique. We took screenshots of the app and extracted the RGB values from the product image section. By comparing these values with the expected reference image, we could determine if the image was correctly displayed. This method allowed us to validate image presence without relying on traditional UI identifiers. RGB validation proved to be a reliable solution in this scenario.

Color Variations: Different devices or screen configurations may render colors differently, requiring a tolerance or range of acceptable RGB values.

Different Testing Environments-os: The eCommerce platform supports automation testing for Android and Automation testing for iOS applications, ensuring seamless functionality across different operating systems is a key challenge in the software testing process. With a diverse customer base using a variety of devices.

Case Study Example: Verifying Product Image Colors

Let’s say to perform automation testing in our mobile applications we need to first verify that a product image in a mobile app is colored black or something else. Here’s how the steps would work in a real-world scenario:

1. Capture a screenshot of the application’s screen containing that product image.
2. Crop the screenshot to used to isolate the area where the product is located.
3. Extract the RGB value from the pixel where the product is located.
4. Compare the extracted RGB value with the expected RGB value for green (e.g., (0, 255, 0)).
5. If the values match, the test passes; otherwise, it fails.

Advantages of RGB Finding via Image Crop

• Efficiency: By cropping the image, you can focus on only the necessary parts of the screen, making the process which is more efficient and faster.
• Accuracy: RGB comparisons help you provide a more precise way to verify color correctness compared to methods like region-based comparisons or UI element checks.

Conclusion

The RGB finding via image crop in Appium provides a powerful and efficient way to validate the visual aspects for mobile application testing. By leveraging image processing and comparing RGB values, testers can ensure that their mobile application meets the expected visual standards. This case study demonstrates how you can use this approach in a real-world scenario to enhance the effectiveness of your automation testing.