old_contents: if __name__ == '__main__':
      from NeuroIO import NeuroIO
      from PreProcess import PreProcess
      from Cluster import Cluster
  
      neuroread = NeuroIO(r"C:\Users\USERNAME\Downloads\Brainbow-demo.tif")
      img_data = neuroread.img_data_return()[0]
      img_path = neuroread.img_data_return()[1]
      pre_processed_data = PreProcess(im_data=img_data, filepath=img_path, snapshotpath=r"C:\UROP\\", multiprocess=True,
                                      cores="auto")
      pre_processed_data.blur(blur_sigma=0.5, xyz_scale=(1, 1, 1))
      pre_processed_data.find_threshold(method="isodata", snapshot=True)
      refined_mask = pre_processed_data.sobel_watershed(threshold="last", snapshot=True)
      pre_processed_data.lab_mode()
      img_lab = pre_processed_data.return_data()
      segment = Cluster(img_data=img_lab, mask=refined_mask)
      cluster_results = segment.DBSCAN(start_frame=0, end_frame=100, size_threshold=75, max_dist=19, min_samp=10,
                                       dist_weight=3.0,
                                       color_weight=18.0, metric="euclidean", algo="ball_tree")
      neuroread.img_data_write(cluster_results, "C:\Users\USERNAME\Desktop\\")
  
new_contents: if __name__ == '__main__':
      from NeuroIO import NeuroIO
      from PreProcess import PreProcess
      from Cluster import Cluster
  
      neuroread = NeuroIO(r"C:\Users\USERNAME\Downloads\Brainbow-demo.tif")
      img_data = neuroread.img_data_return()[0]
      img_path = neuroread.img_data_return()[1]
      pre_processed_data = PreProcess(im_data=img_data, filepath=img_path, snapshotpath=r"C:\UROP\\",
                                      multiprocess=True, cores="auto")
      pre_processed_data.blur(blur_sigma=0.5, xyz_scale=(1, 1, 1))
      pre_processed_data.find_threshold(method="isodata", snapshot=True)
      refined_mask = pre_processed_data.sobel_watershed(threshold="last", snapshot=True)
      pre_processed_data.lab_mode()
      img_lab = pre_processed_data.return_data()
      segment = Cluster(img_data=img_lab, mask=refined_mask)
      cluster_results = segment.super_pixel(start_frame=0, end_frame=100, size_threshold=75, max_dist=19, min_samp=10,
                                            dist_weight=3.0, color_weight=18.0, metric="euclidean", algo="auto",
                                            multiprocess=True, num_cores="auto", num_slices=4)
      neuroread.img_data_write(cluster_results, "C:\Users\USERNAME\Desktop\\")
  
subject: Enable support for the parallel dbscan.