Detects areas in focus in photos, by searching for sharpest areas and then enlarging them. Focus Detection works by converting the ouput of an high-pass filter to a mask.
At the moment, the only dependencies are numpy and opencv. To install the package just do
pip install .
Output is a file with same extension as the original file with a name suffix '_focus'
### run on a single image
python process.py -i input_image.jpg
### run on a directory of images
python process.py -i input_directory/
The algorithm used for detection is still under development. At the moment there are two main free parameters:
-
high_pass_size sets the Gaussian Blur kernel size of the High Pass Filter (strength of the high-pass filter). Higher values lead to a more aggressive separation between in-focus and out-of-focus areas.
-
in_focus_regions sets how many countours the recursive median blur filter should stop, ie. how many disjoint in-focus areas we want to allow in the final mask. Values of 1 and 2 may lead to over-application of median blur recursively and shrinking of focus areas found.
Experiments on 20MP images suggest values of high_pass_size=12 and in_focus_regions=3.
- Build an evaluation dataset, including images with different resolution
- Train the algorithms by optimising the parameters.
- Test different kernels for the initial step.
BurDetection2 by Will Brennan.
