apply_median_filter
- ketos.audio.utils.filter.apply_median_filter(img, row_factor=3, col_factor=4)[source]
Discard pixels that are lower than the median threshold.
The resulting image will have 0s for pixels below the threshold and 1s for the pixels above the threshold.
- Note: Code adapted from Kahl et al. (2017)
Paper: http://ceur-ws.org/Vol-1866/paper_143.pdf Code: https://github.com/kahst/BirdCLEF2017/blob/master/birdCLEF_spec.py
- Args:
- imgnumpy array
Array containing the img to be filtered. OBS: Note that contents of img are modified by call to function.
- row_factor: int or float
Factor by which the row-wise median pixel value will be multiplied in orther to define the threshold.
- col_factor: int or float
Factor by which the col-wise median pixel value will be multiplied in orther to define the threshold.
- Returns:
- filtered_img: numpy array
The filtered image with 0s and 1s.
- Example:
>>> from ketos.audio.utils.filter import apply_median_filter >>> img = np.array([[1,4,5], ... [3,5,1], ... [1,0,9]]) >>> img_fil = apply_median_filter(img, row_factor=1, col_factor=1) >>> print(img_fil) [[0 0 0] [0 1 0] [0 0 1]]