A console/terminal demo of the OpenCV basic linear transform for brightness and contrast, supporting Windows 11 and Ubuntu Linux 24.04. Each pixel is computed as new = clip(alpha × src + beta, 0, 255), where alpha scales the contrast and beta shifts the brightness, with values clipped to the 0 to 255 range. Two example images ship under data/ (Lena and sample), and the result is saved to model/brightness/. No GPU is involved.

 

[Folder Structure]

  • CLAUDE.md / AGENT.md: program specification (identical content).
  • CHANGELOG.md: change log.
  • copyright.txt: copyright notice.
  • data/: the example images Lena.png and sample.png.
  • model/brightness/: the result brightness.png; the Lena example is included.
  • tool/tools.py: shared helpers.
  • src/: the demo, the launcher scripts and this document.
  • venv/: Python virtual environment, created by step 01.

[Prerequisites]

  • Operating system: Windows 11 or Ubuntu Linux 24.04.
  • Python 3 and pip.
  • No GPU required; an ordinary CPU is enough.

[Instructions]

Step 1: Create the virtual environment

Delete the old venv/, create a fresh one and install the packages listed in src/requirements.txt. The script aborts loudly if pip fails.

 

Windows: src\01_venv_create.bat

Linux: bash src/01_venv_create.sh

Step 2: Activate the virtual environment

Activate the venv. On Linux, source the script.

 

Windows: src\02_venv_activate.bat

Linux: source src/02_venv_activate.sh

Step 3: Adjust the brightness and contrast

Run the brightness and contrast demo. Any extra arguments are forwarded to the program.

 

Windows: src\03_brightness.bat

Linux: bash src/03_brightness.sh

To use your own image and parameters, for example:

bash src/03_brightness.sh --source data/sample.png --alpha 1.2 --beta 80

 

Step 4: Remove the virtual environment

Delete the venv/ folder.

 

Windows: src\99_venv_clear.bat

Linux: bash src/99_venv_clear.sh

[Python Entry Point]

  • src/brightness.py: [--source IMG] [--alpha 2.0] [--beta 50] [--output-dir DIR] [--show]. alpha is the contrast factor (a useful range is 1.0 to 3.0) and beta the brightness offset (0 to 100). The earlier example prompted for these two values interactively; here they are arguments. It saves brightness.png to model/brightness/; --show also opens the result in a window. Large alpha values saturate the bright channels by design.

[References]

 

This SDK is built in AppForAI - AI Dev Tools.

 

Purchase license separately:  USD 600, permanent authorization, single APP authorization, single machine authorization, one-year activation, one-year download, one-year update, one-year email technical support.