Description:
The current face detection logic in main.py does not perform well under certain lighting conditions and with images at extreme angles. This reduces the model's overall accuracy and negatively impacts the user experience.

Changes Required
I propose modifying the detection pipeline to include additional image preprocessing steps, such as:

• Brightness normalization to handle low-light conditions( I will use opencv python library for enhancement)
• Rotation correction to detect faces captured at different angles.(I will call a function to rotate the images for better angle and better quality of images)

These enhancements will improve detection accuracy, particularly in challenging conditions.

Affected Files:

1. main.py: I want to update the face detection logic to incorporate new preprocessing steps before feeding images into the model.
2. index.js: I also want to modify the frontend logic to ensure that the uploaded images are preprocessed (e.g., rotated if needed) before being sent to the backend for detection for more user friendly.