Feature/resize image

[dengjianbo3]

Image Processing Enhancements: Resize and Compress Functionality

Description

This PR introduces improvements to our image processing capabilities, adding both resize and compress functionalities to the save_base64_image action. These enhancements allow for more efficient storage and transmission of images within our system.

Key Changes:

1. Added resize_image function to adjust image dimensions while maintaining aspect ratio.
2. Implemented compress_image function to reduce image file size with adjustable quality.
3. Updated save_base64_image to incorporate optional resizing and compression.

Implementation Details

• resize_image: Uses PIL's LANCZOS resampling for high-quality resizing.
• compress_image: Utilizes JPEG compression with adjustable quality settings.
• save_base64_image: Now accepts optional ratio and quality parameters for resizing and compression, respectively.

Testing Methodology

A comprehensive test suite (TestSaveBase64Image) has been implemented to verify the functionality:

1. test_save_image_without_resize_or_compression: Ensures basic image saving works correctly.
2. test_save_image_with_resize: Verifies resizing functionality (20% of original size).
3. test_save_image_with_compression: Tests compression capability (quality set to 20).
4. test_save_image_with_resize_and_compression: Combines both resizing and compression.

Tests use a sample image and check for:

• Correct file creation
• Appropriate image dimensions after processing
• Proper format conversion (PNG/JPEG as needed)
• File size reduction (implicitly tested through compression)

Error logging has been implemented to facilitate debugging and ensure test reliability.

How to Test

1. Ensure you have the required dependencies (PIL, etc.) installed.
2. Place a test image in the test_images directory (e.g., test_image.png).
3. Run the test suite: python test_resize_image.py
4. Check the test_images directory for output files, particularly:
   • test_resized_image.png: Resized version of the original image
   • test_compressed_image.jpg: Compressed version of the original image
   • test_resized_compressed_image.jpg: Resized and compressed version
5. Compare file sizes, dimensions, and visual quality of the processed images.

Important Note on Resize and Compression Parameters

The current implementation uses fixed values (resize ratio of 0.2 and compression quality of 20) for testing purposes. However, it's crucial to note that optimal parameters can vary significantly depending on the specific use case and requirements of the system. To determine the best settings:

1. Conduct real-world tests with a diverse set of images typical to your application.
2. Evaluate the processed images using relevant metrics (e.g., file size reduction, visual quality, processing time, dimension accuracy).
3. If applicable, perform recognition or processing tests on the resized and compressed images to ensure they meet the required quality standards for your specific use case.
4. Based on these tests, adjust the resize ratio and compression quality parameters to find the optimal balance between file size reduction, dimension requirements, and maintaining necessary image quality for your application.

Additionally, it's important to consider that screenshots from different devices may require different processing parameters:

5. Test the resize and compression functions with screenshots from various devices (e.g., different smartphones, tablets, desktop computers) as their native resolutions and image characteristics can vary significantly.
6. Analyze how different device screenshots respond to resizing and compression, and consider implementing device-specific parameter sets if necessary.
7. For applications dealing with a wide range of devices, consider implementing an adaptive algorithm that can adjust parameters based on the input image's characteristics (resolution, DPI, etc.) to ensure optimal results across different devices.

This device-specific consideration is particularly important for maintaining consistency and quality across different platforms and ensuring that the processed images meet the requirements for all target devices and use cases.

Please review and provide feedback on these image processing enhancements, keeping in mind the need for real-world testing and optimization for both resize and compress functionalities.