Datasets:
Kurt Stolle
commited on
Commit
·
0bb73c7
1
Parent(s):
4849086
Minor readability improvements
Browse files- examples.ipynb +24 -113
- scripts/build.py +3 -0
examples.ipynb
CHANGED
@@ -14,7 +14,7 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [
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{
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@@ -22,110 +22,20 @@
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"output_type": "stream",
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"text": [
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"Sample csvps-val/000030\n",
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-
"
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"
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-
"
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"
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" False, True],\n",
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" 'number': ['000000', '000001', '000002', '000003', '000004',\n",
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-
" '000005', '000006', '000007', '000008', '000009',\n",
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" '000010', '000011', '000012', '000013', '000014',\n",
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" '000015', '000016', '000017', '000018', '000019',\n",
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-
" '000020', '000021', '000022', '000023', '000024',\n",
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-
" '000025', '000026', '000027', '000028', '000029'],\n",
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-
" 'primary_key': ['lindau_000037_000000', 'lindau_000037_000001',\n",
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" 'lindau_000037_000002', 'lindau_000037_000003',\n",
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" 'lindau_000037_000004', 'lindau_000037_000005',\n",
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" 'lindau_000037_000006', 'lindau_000037_000007',\n",
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" 'lindau_000037_000008', 'lindau_000037_000009',\n",
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" 'lindau_000037_000010', 'lindau_000037_000011',\n",
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" 'lindau_000037_000012', 'lindau_000037_000013',\n",
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" 'lindau_000037_000014', 'lindau_000037_000015',\n",
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-
" 'lindau_000037_000016', 'lindau_000037_000017',\n",
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-
" 'lindau_000037_000018', 'lindau_000037_000019',\n",
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" 'lindau_000037_000020', 'lindau_000037_000021',\n",
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" 'lindau_000037_000022', 'lindau_000037_000023',\n",
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" 'lindau_000037_000024', 'lindau_000037_000025',\n",
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" 'lindau_000037_000026', 'lindau_000037_000027',\n",
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" 'lindau_000037_000028', 'lindau_000037_000029'],\n",
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" 'timestamps': [0, 58925424, 117850824, 176776224, 235701592,\n",
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" 294627064, 353552488, 412478000, 471403416,\n",
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" 530328888, 589254288, 648179664, 707105072,\n",
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" 766030408, 824955840, 883881184, 942806640,\n",
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" 1001732056, 1060657528, 1119582984, 1178508320,\n",
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" 1237433744, 1296359088, 1355284520, 1414209856,\n",
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" 1473135304, 1532060720, 1590986120, 1649911576,\n",
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" 1708836952]}}\n",
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"Sample csvps-val/000031\n",
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"
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"
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"
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"
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" False, True],\n",
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" 'number': ['000000', '000001', '000002', '000003', '000004',\n",
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" '000005', '000006', '000007', '000008', '000009',\n",
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" '000010', '000011', '000012', '000013', '000014',\n",
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" '000015', '000016', '000017', '000018', '000019',\n",
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" '000020', '000021', '000022', '000023', '000024',\n",
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" '000025', '000026', '000027', '000028', '000029'],\n",
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" 'primary_key': ['lindau_000047_000000', 'lindau_000047_000001',\n",
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" 'lindau_000047_000002', 'lindau_000047_000003',\n",
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" 'lindau_000047_000004', 'lindau_000047_000005',\n",
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" 'lindau_000047_000006', 'lindau_000047_000007',\n",
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" 'lindau_000047_000008', 'lindau_000047_000009',\n",
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" 'lindau_000047_000010', 'lindau_000047_000011',\n",
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" 'lindau_000047_000012', 'lindau_000047_000013',\n",
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" 'lindau_000047_000014', 'lindau_000047_000015',\n",
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" 'lindau_000047_000016', 'lindau_000047_000017',\n",
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" 'lindau_000047_000018', 'lindau_000047_000019',\n",
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" 'lindau_000047_000020', 'lindau_000047_000021',\n",
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" 'lindau_000047_000022', 'lindau_000047_000023',\n",
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" 'lindau_000047_000024', 'lindau_000047_000025',\n",
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" 'lindau_000047_000026', 'lindau_000047_000027',\n",
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" 'lindau_000047_000028', 'lindau_000047_000029'],\n",
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" 'timestamps': [0, 58925416, 117850784, 176776216, 235701560,\n",
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" 294627000, 353552352, 412477776, 471403168,\n",
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" 530328552, 589253984, 648179336, 707104784,\n",
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" 766030160, 824955608, 883880992, 942806400,\n",
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" 1001731832, 1060657200, 1119582648, 1178508008,\n",
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" 1237433456, 1296358824, 1355284248, 1414209648,\n",
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" 1473135024, 1532060464, 1590985824, 1649911272,\n",
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" 1708836624]}}\n",
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"Sample csvps-val/000032\n",
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"
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"
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" False, True],\n",
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" 'number': ['000000', '000001', '000002', '000003', '000004',\n",
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" '000005', '000006', '000007', '000008', '000009',\n",
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" '000010', '000011', '000012', '000013', '000014',\n",
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" '000015', '000016', '000017', '000018', '000019',\n",
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" '000020', '000021', '000022', '000023', '000024',\n",
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" '000025', '000026', '000027', '000028', '000029'],\n",
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" 'primary_key': ['lindau_000057_000000', 'lindau_000057_000001',\n",
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" 'lindau_000057_000002', 'lindau_000057_000003',\n",
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" 'lindau_000057_000004', 'lindau_000057_000005',\n",
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" 'lindau_000057_000006', 'lindau_000057_000007',\n",
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" 'lindau_000057_000008', 'lindau_000057_000009',\n",
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" 'lindau_000057_000010', 'lindau_000057_000011',\n",
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" 'lindau_000057_000012', 'lindau_000057_000013',\n",
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" 'lindau_000057_000014', 'lindau_000057_000015',\n",
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" 'lindau_000057_000016', 'lindau_000057_000017',\n",
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" 'lindau_000057_000018', 'lindau_000057_000019',\n",
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" 'lindau_000057_000020', 'lindau_000057_000021',\n",
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" 'lindau_000057_000022', 'lindau_000057_000023',\n",
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" 'lindau_000057_000024', 'lindau_000057_000025',\n",
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" 'lindau_000057_000026', 'lindau_000057_000027',\n",
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" 'lindau_000057_000028', 'lindau_000057_000029'],\n",
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" 'timestamps': [0, 58925896, 117851752, 176777576, 235703424,\n",
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" 294629232, 353555104, 412480888, 471406760,\n",
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" 530332656, 589258512, 648184360, 707110176,\n",
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" 766036096, 824961936, 883887864, 942813704,\n",
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" 1001739592, 1060665480, 1119591288, 1178517152,\n",
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" 1237442936, 1296368816, 1355294616, 1414220496,\n",
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" 1473146352, 1532072200, 1590998064, 1649923840,\n",
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" 1708849704]}}\n"
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]
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}
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],
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@@ -144,7 +54,7 @@
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"for i, sample in enumerate(ds):\n",
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" if i > 2: \n",
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" break\n",
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" meta_data = json.loads(sample[\"json\"].decode())\n",
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" print(\"Sample \" + sample[\"__key__\"])\n",
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" print(pformat(meta_data, compact=True))\n",
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" "
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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{
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"text": [
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"__key__ (<class 'str'>) csvps-val/000030/000000:000001\n",
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"camera.json (<class 'bytes'>) ...\n",
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"json (<class '
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"
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"depth.tiff (<class 'list'>) 2\n",
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"image.png (<class 'list'>) 2\n",
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"
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]
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}
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],
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"import collections\n",
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"import itertools\n",
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"\n",
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"def find_frame_keys(keys):\n",
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" r\"\"\"\n",
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" Returns a mapping from frame number to the keys of the sample that correspond to \n",
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" that frame.\n",
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" meta_keys.add(key)\n",
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" continue \n",
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" stem, other = key.split(\".\", 1)\n",
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" if stem
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" frame_keys[stem].append(other)\n",
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" else:\n",
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" meta_keys.add(key)\n",
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"\n",
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"def generate_range(src, length: int = 2, *, missing_ok: bool =True):\n",
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" for sample in src:\n",
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" key = sample[\"__key__\"]\n",
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" frame_keys, meta_keys = find_frame_keys(sample.keys()) \n",
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" \n",
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" pair_keys = set(itertools.chain.from_iterable(frame_keys.values()))\n",
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" meta_data = {key: sample[key] for key in meta_keys}\n",
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Sample csvps-val/000030\n",
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"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
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" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
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" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
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" '000024', '000025', '000026', '000027', '000028', '000029']\n",
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"Sample csvps-val/000031\n",
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"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
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" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
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" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
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" '000024', '000025', '000026', '000027', '000028', '000029']\n",
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"Sample csvps-val/000032\n",
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"['000000', '000001', '000002', '000003', '000004', '000005', '000006', '000007',\n",
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" '000008', '000009', '000010', '000011', '000012', '000013', '000014', '000015',\n",
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" '000016', '000017', '000018', '000019', '000020', '000021', '000022', '000023',\n",
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" '000024', '000025', '000026', '000027', '000028', '000029']\n"
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]
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}
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],
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"for i, sample in enumerate(ds):\n",
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" if i > 2: \n",
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" break\n",
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" meta_data = json.loads(sample[\"frames.json\"].decode())\n",
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" print(\"Sample \" + sample[\"__key__\"])\n",
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" print(pformat(meta_data, compact=True))\n",
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" "
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"text": [
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"__key__ (<class 'str'>) csvps-val/000030/000000:000001\n",
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"camera.json (<class 'bytes'>) ...\n",
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"metadata.json (<class 'list'>) 2\n",
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"vehicle.json (<class 'list'>) 2\n",
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"image.png (<class 'list'>) 2\n",
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"panoptic.png (<class 'list'>) 2\n",
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"depth.tiff (<class 'list'>) 2\n"
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]
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}
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],
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"import collections\n",
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"import itertools\n",
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"\n",
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"def find_frame_keys(keys, frames):\n",
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" r\"\"\"\n",
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" Returns a mapping from frame number to the keys of the sample that correspond to \n",
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" that frame.\n",
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" meta_keys.add(key)\n",
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" continue \n",
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" stem, other = key.split(\".\", 1)\n",
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" if stem in frames:\n",
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" frame_keys[stem].append(other)\n",
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" else:\n",
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" meta_keys.add(key)\n",
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"\n",
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"def generate_range(src, length: int = 2, *, missing_ok: bool =True):\n",
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" for sample in src:\n",
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" frames = json.loads(sample.pop(\"frames.json\").decode())\n",
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" key = sample[\"__key__\"]\n",
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" frame_keys, meta_keys = find_frame_keys(sample.keys(), frames) \n",
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" \n",
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" pair_keys = set(itertools.chain.from_iterable(frame_keys.values()))\n",
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" meta_data = {key: sample[key] for key in meta_keys}\n",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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scripts/build.py
CHANGED
@@ -57,6 +57,7 @@ def parse_args():
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ap.add_argument(
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"--splits", nargs="+", default=["train", "val", "test"], help="Splits to build."
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)
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# Positional
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ap.add_argument("manifest", type=Path, help="Path to the manifest CSV file.")
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*,
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data_dir: Path,
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dataset_name: str,
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missing_ok: bool = False,
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frame_inputs: T.Sequence[str] = ("image.png", "vehicle.json"),
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frame_annotations: T.Sequence[str] = ("panoptic.png", "depth.tiff"),
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shard_size=args.shard_size,
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dataset_name=f"{args.name}-{split_out}",
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missing_ok=True,
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)
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ap.add_argument(
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"--splits", nargs="+", default=["train", "val", "test"], help="Splits to build."
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)
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ap.add_argument("--compression", "-c", default="", help="Compression to use")
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# Positional
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ap.add_argument("manifest", type=Path, help="Path to the manifest CSV file.")
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*,
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data_dir: Path,
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dataset_name: str,
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compression: str,
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missing_ok: bool = False,
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frame_inputs: T.Sequence[str] = ("image.png", "vehicle.json"),
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frame_annotations: T.Sequence[str] = ("panoptic.png", "depth.tiff"),
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shard_size=args.shard_size,
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dataset_name=f"{args.name}-{split_out}",
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missing_ok=True,
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compression=args.compression
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)
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