USE.md

⚙️ Configuration

The application uses a configuration file (config.json) to store user settings. Users can specify the following options: To streamline your setup process, you can duplicate the default configuration provided and customize it within your project directory.

• Directories:
  • input_directory: Path to the directory containing input images.
  • output_directory: Path to the directory where processed images will be saved.
• Processing Settings:
  • upscale_factor: Factor by which to upscale images.
  • contrast_factor: Factor to adjust contrast.
  • color_factor: Factor to adjust color.
  • watermark_text: Text for watermarking images.
  • watermark_position: Position of the watermark (e.g., bottom_right).
  • format_conversion: Desired output format (e.g., PNG, JPEG).
  • crop_settings: Coordinates for cropping images (left, top, right, bottom).
  • resize_settings: Dimensions for resizing images (width, height).
  • rotation_angle: Angle for rotating images.
  • flip_mode: Mode for flipping images (horizontal or vertical).
  • noise_reduction: Enable/disable noise reduction.
  • histogram_equalization: Enable/disable histogram equalization.
  • sepia_filter: Enable/disable sepia filter.
  • vignette_filter: Enable/disable vignette filter.
  • face_detection: Enable/disable face detection.
  • background_removal: Enable/disable background removal.
  • compression_quality: Quality setting for image compression (1-100).
  • preserve_metadata: Enable/disable metadata preservation.

☑️ Implementation

The project is organized into several modules, each responsible for different aspects of image processing:

• config.py: Loads the configuration file and provides default settings if the configuration file is not found or invalid.
• file_utils.py: Handles loading images from the specified input directory.
• filters.py: Contains functions to apply various filters to images (e.g., sepia, vignette, histogram equalization).
• main.py: The main script that orchestrates the entire image processing workflow, including loading configuration, processing images, and saving the results.
• metadata.py: Handles the preservation of image metadata during processing.
• notifications.py: Sends desktop notifications to inform the user about the completion of tasks.
• transformations.py: Implements functions for face detection and drawing rectangles around detected faces.

Usage

To use the ImageUpscaler application, follow these steps:

1. Setup Configuration:

   • Run the application. If the configuration file (config.json) does not exist, the application will prompt you to create one by entering various settings.

2. Load Images:

   • The application will load images from the specified input directory.

3. Process Images:

   • Images will be processed according to the settings in the configuration file, applying all specified transformations and enhancements.

4. Save Images:

   • Processed images will be saved to the specified output directory.

5. Receive Notifications:

   • Upon completion, a desktop notification will be sent.

Example Configuration

Here is an example of a config.json file:

{
    "input_directory": "imageUpscaler/input_folder/",
    "output_directory": "imageUpscaler/output/",
    "upscale_factor": 1.0,
    "contrast_factor": 1.0,
    "color_factor": 1.0,
    "watermark_text": "",
    "watermark_position": "bottom_right",
    "format_conversion": "JPEG",
    "crop_settings": [
        0,
        0,
        0,
        0
    ],
    "resize_settings": [
        0,
        0
    ],
    "rotation_angle": 0,
    "flip_mode": "",
    "noise_reduction": true,
    "histogram_equalization": true,
    "sepia_filter": true,
    "vignette_filter": true,
    "face_detection": true,
    "background_removal": false,
    "compression_quality": 85,
    "preserve_metadata": true
}

Happy Coding!!