text: # pip install supervisely
  import supervisely_lib as sly
  import numpy as np
  import os
  from PIL import Image
  from tqdm import tqdm
  
  # Download dataset from <https://supervise.ly/explore/projects/supervisely-person-dataset-23304/datasets>
  project_root = "PATH_TO/Supervisely Person Dataset"  # <-- Configure input
  project = sly.Project(project_root, sly.OpenMode.READ)
  
  output_path = "OUTPUT_DIR"  # <-- Configure output
  os.makedirs(os.path.join(output_path, "train", "src"))
  os.makedirs(os.path.join(output_path, "train", "msk"))
  os.makedirs(os.path.join(output_path, "valid", "src"))
  os.makedirs(os.path.join(output_path, "valid", "msk"))
  
  max_size = 2048  # <-- Configure max size
  
  for dataset in project.datasets:
      for item in tqdm(dataset):
          ann = sly.Annotation.load_json_file(dataset.get_ann_path(item), project.meta)
          msk = np.zeros(ann.img_size, dtype=np.uint8)
          for label in ann.labels:
              label.geometry.draw(msk, color=[255])
          msk = Image.fromarray(msk)
  
          img = Image.open(dataset.get_img_path(item)).convert("RGB")
          if img.size[0] > max_size or img.size[1] > max_size:
              scale = max_size / max(img.size)
              img = img.resize(
                  (int(img.size[0] * scale), int(img.size[1] * scale)), Image.BILINEAR
              )
              msk = msk.resize(
                  (int(msk.size[0] * scale), int(msk.size[1] * scale)), Image.NEAREST
              )
  
          img.save(
              os.path.join(output_path, "train", "src", item.replace(".png", ".jpg"))
          )
          msk.save(
              os.path.join(output_path, "train", "msk", item.replace(".png", ".jpg"))
          )
  
  # Move first 100 to validation set
  names = os.listdir(os.path.join(output_path, "train", "src"))
  for name in tqdm(names[:100]):
      os.rename(
          os.path.join(output_path, "train", "src", name),
          os.path.join(output_path, "valid", "src", name),
      )
      os.rename(
          os.path.join(output_path, "train", "msk", name),
          os.path.join(output_path, "valid", "msk", name),
      )
  