python - Filtering a labeled image by particle area

Question

I have a labeled image of detected particles and a dataframe with the corresponding area of each labeled particle. What I want to do is filter out every particle on the image with an area smaller than a specified value.

I got it working with the example below, but I know there must be a smarter and especially faster way. For example skipping the loop by comparing the image with the array.

Thanks for your help!

Example:

labels = df["label"][df.area > 5000].to_numpy()
mask = np.zeros(labeled_image.shape)
for label in labels:
    mask[labeled_image == label] = 1

Dataframe:

      label  centroid-0  centroid-1  area
0         1          15        3681   191
1         2          13        1345   390
2         3          43        3746   885
3         4          32        3616   817
4         5          20        4250   137
    ...         ...         ...   ...
3827   3828        4149        1620   130
3828   3829        4151         852    62
3829   3830        4155         330   236
3830   3831        4157         530   377
3831   3832        4159        3975    81

question from:https://stackoverflow.com/questions/65599349/filtering-a-labeled-image-by-particle-area

Answer 1

You can use isin to check equality to several labels. The resulting boolean array can be directly used as the mask after casting to the required type (e.g. int):

labels = df.loc[df.area.gt(5000), 'label']
mask = np.isin(labeled_image, labels).astype(int)