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""" |
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NOTE: Major TOM standard does not require any specific type of thumbnail to be computed. |
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Instead these are shared as optional help since this is how the Core dataset thumbnails have been computed. |
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""" |
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from rasterio.io import MemoryFile |
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from PIL import Image |
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import numpy as np |
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def s2l2a_thumbnail(B04, B03, B02, gain=1.3, gamma=0.6): |
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""" |
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Takes B04, B03, B02 numpy arrays along with the corresponding NODATA values (default is -32768.0) |
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Returns a numpy array with the thumbnail |
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""" |
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thumb = np.stack([B04, B03, B02], -1) |
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thumb = gain*((thumb/10_000)**gamma) |
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return (thumb.clip(0,1)*255).astype(np.uint8) |
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def s2l2a_thumbnail_from_datarow(datarow): |
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""" |
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Takes a datarow directly from one of the data parquet files |
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Returns a PIL Image |
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""" |
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with MemoryFile(datarow['B04'][0].as_py()) as mem_f: |
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with mem_f.open(driver='GTiff') as f: |
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B04=f.read().squeeze() |
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B04_NODATA = f.nodata |
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with MemoryFile(datarow['B03'][0].as_py()) as mem_f: |
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with mem_f.open(driver='GTiff') as f: |
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B03=f.read().squeeze() |
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B03_NODATA = f.nodata |
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with MemoryFile(datarow['B02'][0].as_py()) as mem_f: |
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with mem_f.open(driver='GTiff') as f: |
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B02=f.read().squeeze() |
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B02_NODATA = f.nodata |
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img = s2l2a_thumbnail(B04,B03,B02) |
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return Image.fromarray(img) |
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if __name__ == '__main__': |
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from fsspec.parquet import open_parquet_file |
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import pyarrow.parquet as pq |
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print('[example run] reading file from HuggingFace...') |
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url = "https://huggingface.co/datasets/Major-TOM/Core-S2L2A/resolve/main/images/part_01000.parquet" |
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with open_parquet_file(url, columns = ["B04", "B03", "B02"]) as f: |
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with pq.ParquetFile(f) as pf: |
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first_row_group = pf.read_row_group(1, columns = ["B04", "B03", "B02"]) |
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print('[example run] computing the thumbnail...') |
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thumbnail = s2l2a_thumbnail_from_datarow(first_row_group) |
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thumbnail.save('example_thumbnail.png', format = 'PNG') |