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Datasets:
AstroCompress
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SBI-16-3D

Tags:
astronomy
compression
images
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Dataset card Files Community
rithwiks commited on
Commit
0733e6e
•
1 Parent(s): 35db85e

added read pattern to splits. updated version

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Files changed (6) hide show
  1. SBI-16-3D.py +1 -1
  2. splits/full_test.jsonl +0 -0
  3. splits/full_train.jsonl +0 -0
  4. splits/tiny_test.jsonl +1 -1
  5. splits/tiny_train.jsonl +2 -2
  6. utils/create_splits.py +2 -1
SBI-16-3D.py CHANGED
@@ -41,7 +41,7 @@ _REPO_ID = "AstroCompress/SBI-16-3D"
41
  class SBI_16_3D(datasets.GeneratorBasedBuilder):
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  """SBI-16-3D Dataset"""
43
 
44
- VERSION = datasets.Version("1.0.2")
45
 
46
  BUILDER_CONFIGS = [
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  datasets.BuilderConfig(
 
41
  class SBI_16_3D(datasets.GeneratorBasedBuilder):
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  """SBI-16-3D Dataset"""
43
 
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+ VERSION = datasets.Version("1.0.3")
45
 
46
  BUILDER_CONFIGS = [
47
  datasets.BuilderConfig(
splits/full_test.jsonl CHANGED
The diff for this file is too large to render. See raw diff
 
splits/full_train.jsonl CHANGED
The diff for this file is too large to render. See raw diff
 
splits/tiny_test.jsonl CHANGED
@@ -1 +1 @@
1
- {"image_id": "jw01181006001_18201_00001_nrcb3_uncal", "image": "./data/jw01181006001_18201_00001_nrcb3_uncal.fits", "ra": 189.29522579682242, "dec": 62.170810657813895, "pixscale": 8.575886111111111e-06, "ntimes": 5, "footprint": [189.30240387763766, 62.182778659588344, 189.26965845442572, 62.17416743800172, 189.2880533944291, 62.15884228507122, 189.32078746079904, 62.167449168520186]}
 
1
+ {"image_id": "jw01181006001_18201_00001_nrcb3_uncal", "image": "./data/jw01181006001_18201_00001_nrcb3_uncal.fits", "ra": 189.29522579682242, "dec": 62.170810657813895, "pixscale": 8.575886111111111e-06, "ntimes": 5, "read_pattern": "DEEP8", "footprint": [189.30240387763766, 62.182778659588344, 189.26965845442572, 62.17416743800172, 189.2880533944291, 62.15884228507122, 189.32078746079904, 62.167449168520186]}
splits/tiny_train.jsonl CHANGED
@@ -1,2 +1,2 @@
1
- {"image_id": "jw02736001001_02105_00002_nrcb2_uncal", "image": "./data/jw02736001001_02105_00002_nrcb2_uncal.fits", "ra": 110.83192206560962, "dec": -73.43953078693673, "pixscale": 8.66568472222222e-06, "ntimes": 8, "footprint": [110.78883025365087, -73.43716349365775, 110.82367419417301, -73.45188632192357, 110.87502583164303, -73.44188922346261, 110.840157982959, -73.42717492804437]}
2
- {"image_id": "jw02128002001_04201_00001_nrcb3_uncal", "image": "./data/jw02128002001_04201_00001_nrcb3_uncal.fits", "ra": 24.094268349401542, "dec": 30.671409367815368, "pixscale": 8.575886111111111e-06, "ntimes": 2, "footprint": [24.098127118715173, 30.683386215331247, 24.08038220809025, 30.674736549930312, 24.09041053675658, 30.659432406304237, 24.10815353404423, 30.668080709211786]}
 
1
+ {"image_id": "jw02736001001_02105_00002_nrcb2_uncal", "image": "./data/jw02736001001_02105_00002_nrcb2_uncal.fits", "ra": 110.83192206560962, "dec": -73.43953078693673, "pixscale": 8.66568472222222e-06, "ntimes": 8, "read_pattern": "MEDIUM8", "footprint": [110.78883025365087, -73.43716349365775, 110.82367419417301, -73.45188632192357, 110.87502583164303, -73.44188922346261, 110.840157982959, -73.42717492804437]}
2
+ {"image_id": "jw02128002001_04201_00001_nrcb3_uncal", "image": "./data/jw02128002001_04201_00001_nrcb3_uncal.fits", "ra": 24.094268349401542, "dec": 30.671409367815368, "pixscale": 8.575886111111111e-06, "ntimes": 2, "read_pattern": "SHALLOW2", "footprint": [24.098127118715173, 30.683386215331247, 24.08038220809025, 30.674736549930312, 24.09041053675658, 30.659432406304237, 24.10815353404423, 30.668080709211786]}
utils/create_splits.py CHANGED
@@ -90,10 +90,11 @@ def make_split_jsonl_files(config_type="tiny", data_dir="./data",
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  dec = hdul["SCI"].header.get('CRVAL2', 0)
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  pixscale = calculate_pixel_scale(hdul["SCI"].header)
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  footprint = get_fits_footprint(file)
 
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  # get the number of groups per int
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  ntimes = hdul["SCI"].data.shape[1]
95
  item = {"image_id": image_id, "image": file, "ra": ra, "dec": dec,
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- "pixscale": pixscale, "ntimes": ntimes, "footprint": footprint}
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  out_f.write(json.dumps(item) + "\n")
98
 
99
  create_jsonl(train_files, "train")
 
90
  dec = hdul["SCI"].header.get('CRVAL2', 0)
91
  pixscale = calculate_pixel_scale(hdul["SCI"].header)
92
  footprint = get_fits_footprint(file)
93
+ read_pattern = hdul[0].header.get('READPATT', 0)
94
  # get the number of groups per int
95
  ntimes = hdul["SCI"].data.shape[1]
96
  item = {"image_id": image_id, "image": file, "ra": ra, "dec": dec,
97
+ "pixscale": pixscale, "ntimes": ntimes, "read_pattern": read_pattern, "footprint": footprint}
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  out_f.write(json.dumps(item) + "\n")
99
 
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  create_jsonl(train_files, "train")