Create extras/thumbnail_s1rtc.py

extras/thumbnail_s1rtc.py

@@ -0,0 +1,80 @@
+"""
+    NOTE: Major TOM standard does not require any specific type of thumbnail to be computed.
+    
+    Instead these are shared as optional help since this is how the Core dataset thumbnails have been computed.
+"""
+
+from rasterio.io import MemoryFile
+from PIL import Image
+import numpy as np
+
+def s1rtc_thumbnail(vv, vh, vv_NODATA = -32768.0, vh_NODATA = -32768.0):
+    """
+        Takes vv and vh numpy arrays along with the corresponding NODATA values (default is -32768.0)
+        
+        Returns a numpy array with the thumbnail
+    """
+    
+    # valid data masks
+    vv_mask = vv != vv_NODATA
+    vh_mask = vh != vh_NODATA
+
+    # remove invalid values before log op
+    vv[vv<0] = vv[vv>=0].min()
+    vh[vh<0] = vh[vh>=0].min()
+
+    # apply log op
+    vv_dB = 10*np.log10(vv)
+    vh_dB = 10*np.log10(vh)
+
+    # scale to 0-255
+    vv_dB = (vv_dB - vv_dB[vv_mask].min()) / (vv_dB[vv_mask].max() - vv_dB[vv_mask].min()) * 255
+    vh_dB = (vh_dB - vh_dB[vh_mask].min()) / (vh_dB[vh_mask].max() - vh_dB[vh_mask].min()) * 255
+
+    # represent nodata as 0
+    vv_dB[vv_mask==0] = 0
+    vh_dB[vh_mask==0] = 0
+
+    # false colour composite
+    return np.stack([vv_dB,
+                    255*(vv_dB+vh_dB)/np.max(vv_dB+vh_dB),
+                    vh_dB
+                   ],-1).astype(np.uint8)
+
+def s1rtc_thumbnail_from_datarow(datarow):
+    """
+        Takes a datarow directly from one of the data parquet files
+        
+        Returns a PIL Image
+    """
+
+    with MemoryFile(datarow['vv'][0].as_py()) as mem_f:
+        with mem_f.open(driver='GTiff') as f:
+            vv=f.read().squeeze()
+            vv_NODATA = f.nodata
+    
+    with MemoryFile(datarow['vh'][0].as_py()) as mem_f:
+        with mem_f.open(driver='GTiff') as f:
+            vh=f.read().squeeze()
+            vh_NODATA = f.nodata
+
+    img = s1rtc_thumbnail(vv, vh, vv_NODATA=vv_NODATA, vh_NODATA=vh_NODATA)
+
+    return Image.fromarray(img)
+
+if __name__ == '__main__':    
+    from fsspec.parquet import open_parquet_file
+    import pyarrow.parquet as pq
+
+    print('[example run] reading file from HuggingFace...')
+    url = "https://huggingface.co/datasets/Major-TOM/Core-S1RTC/resolve/main/images/part_00001.parquet"
+    with open_parquet_file(url) as f:
+        with pq.ParquetFile(f) as pf:
+            first_row_group = pf.read_row_group(1)
+    
+    print('[example run] computing the thumbnail...')    
+    thumbnail = s1rtc_thumbnail_from_datarow(first_row_group)
+
+    thumbnail_fname = 'example_thumbnail.png'
+    thumbnail.save(thumbnail_fname, format = 'PNG')
+    print('[example run] saved as "{}"'.format(thumbnail_fname))