6e670b4c66cd96a347e72f14e9380b0606515083,deepmedic/dataManagement/sampling.py,,load_subj_and_get_samples,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,235

Before Change

        // Check if the weight map is fully-zeros. In this case, don"t call the sampling function, just continue.
        // Note that this way, the data loaded on GPU will not be as much as I initially wanted. Thus calculate number-of-batches from this actual number of extracted segments.
        if np.sum(sampling_map>0) == 0 :
            log.print3(id_str+" WARN: Sampling mask/map was found just zeros! No [" + cat_string + "] samples for this subject!")
            continue
        
        coords_of_samples = sample_coords_of_segments(log,
                                            job_i,

After Change

        n_samples_for_cat = n_samples_per_cat[cat_i]
        sampling_map = sampling_maps_per_cat[cat_i]
        // Check if the class is valid for sampling. Invalid if eg there is no such class in the subject"s manual segmentation.
        if not valid_cats[cat_i] :
            log.print3(id_str+" WARN: Invalid sampling category! Sampling map just zeros! No [" + cat_string + "] samples from this subject!")
            assert n_samples_for_cat == 0
            continue
        
        coords_of_samples = sample_coords_of_segments(log,
                                            job_i,
                                            n_samples_for_cat,
                                            dims_highres_segment,

Instances