The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      One or several metadata.csv were found, but not in the same directory or in a parent directory of zip://0000/0.png::hf://datasets/novaia/world-heightmaps-360-v1@7c1fc9de7eea4a38cb6d038587c676ad6b4bbd48/data/0000.zip.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 126, in get_rows_or_raise
                  return get_rows(
                File "/src/services/worker/src/worker/utils.py", line 64, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 103, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1384, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 234, in __iter__
                  yield from self.generate_examples_fn(**self.kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 376, in _generate_examples
                  raise ValueError(
              ValueError: One or several metadata.csv were found, but not in the same directory or in a parent directory of zip://0000/0.png::hf://datasets/novaia/world-heightmaps-360-v1@7c1fc9de7eea4a38cb6d038587c676ad6b4bbd48/data/0000.zip.

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World Heightmaps 360 V1

This is a dataset of 360x360 Earth heightmaps generated from SRTM 1 Arc-Second Global. Each heightmap is labelled according to its latitude and longitude. There are 573,995 samples.

Method

  1. Convert GeoTIFFs into PNGs with Python and Rasterio.
import rasterio
import matplotlib.pyplot as plt
import os

input_directory = '...'
output_directory = '...'
file_list = os.listdir(input_directory)

for i in range(len(file_list)):
    image = rasterio.open(input_directory + file_list[i])
    plt.imsave(output_directory + file_list[i][0:-4] + '.png', image.read(1), cmap='gray')
  1. Split PNGs into 100 patches with Split Image.
from split_image import split_image
import os

input_directory = '...'
output_directory = '...'
file_list = os.listdir(input_directory)

for i in range(len(file_list)):
    split_image(input_directory + file_list[i], 10, 10, should_square=True, should_cleanup=False, output_dir=output_directory)
  1. Hand pick a dataset of corrupted and uncorrupted heightmaps then train a discriminator to automatically filter the whole dataset.
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