Commit ·
cafdb34
1
Parent(s): 3715916
Update LILA.py
Browse files
LILA.py
CHANGED
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@@ -57,9 +57,9 @@ _METADATA_BASE_URL = "https://huggingface.co/datasets/NimaBoscarino/LILA/resolve
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# How do I make these point to the particular commit ID?
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_LILA_URLS = {
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-
"Caltech Camera Traps": "Caltech_Camera_Traps.jsonl",
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"ENA24": "ENA24.jsonl",
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"Missouri Camera Traps": "Missouri_Camera_Traps.jsonl",
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"NACTI": "NACTI.jsonl.zip",
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"WCS Camera Traps": "WCS_Camera_Traps.jsonl.zip",
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"Wellington Camera Traps": "Wellington_Camera_Traps.jsonl.zip",
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@@ -68,15 +68,509 @@ _LILA_URLS = {
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"Idaho Camera Traps": "Idaho_Camera_Traps.jsonl.zip",
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"Snapshot Serengeti": "Snapshot_Serengeti.jsonl.zip",
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"Snapshot Karoo": "Snapshot_Karoo.jsonl.zip",
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-
"Snapshot Kgalagadi": "Snapshot_Kgalagadi.jsonl",
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"Snapshot Enonkishu": "Snapshot_Enonkishu.jsonl.zip",
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"Snapshot Camdeboo": "Snapshot_Camdeboo.jsonl.zip",
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"Snapshot Mountain Zebra": "Snapshot_Mountain_Zebra.jsonl.zip",
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"Snapshot Kruger": "Snapshot_Kruger.jsonl",
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"SWG Camera Traps": "SWG_Camera_Traps.jsonl.zip",
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"Orinoquia Camera Traps": "Orinoquia_Camera_Traps.jsonl.zip",
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}
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class LILAConfig(datasets.BuilderConfig):
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"""Builder Config for LILA"""
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@@ -113,7 +607,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"id": datasets.Value("string"), "file_name": datasets.Value("string"),
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"width": datasets.Value("int32"), "height": datasets.Value("int32"),
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"seq_num_frames": datasets.Value("int32"),
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"date_captured": datasets.Value("
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"seq_id": datasets.Value("string"),
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"location": datasets.Value("string"),
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"rights_holder": datasets.Value("string"),
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@@ -121,6 +615,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"annotations": datasets.Sequence({
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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}),
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"bboxes": datasets.Sequence({
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"id": datasets.Value("string"),
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@@ -137,6 +632,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
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}),
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"image": datasets.Image(decode=False),
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})
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"category_id": datasets.Value("int32"),
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"sequence_level_annotation": datasets.Value("bool"),
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"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
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}),
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"image": datasets.Image(decode=False),
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})
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@@ -162,6 +659,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"annotations": datasets.Sequence({
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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}),
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"bboxes": datasets.Sequence({
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"id": datasets.Value("string"),
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@@ -179,7 +677,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"seq_id": datasets.Value("string"), "country_code": datasets.Value("string"),
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"seq_num_frames": datasets.Value("int32"),
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"status": datasets.Value("string"),
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"datetime": datasets.Value("
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"corrupt": datasets.Value("bool"),
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"annotations": datasets.Sequence({
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"id": datasets.Value("string"),
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@@ -187,6 +685,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"count": datasets.Value("int32"),
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"sex": datasets.Value("string"),
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"age": datasets.Value("string"),
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}),
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"bboxes": datasets.Sequence({
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"id": datasets.Value("string"),
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@@ -201,10 +700,11 @@ class LILA(datasets.GeneratorBasedBuilder):
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"width": datasets.Value("int32"), "height": datasets.Value("int32"),
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"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
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"site": datasets.Value("string"), "camera": datasets.Value("string"),
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"datetime": datasets.Value("
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"annotations": datasets.Sequence({
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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}),
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"image": datasets.Image(decode=False),
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})
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@@ -216,6 +716,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
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}),
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"image": datasets.Image(decode=False),
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})
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@@ -233,6 +734,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"category_id": datasets.Value("int32"),
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"sequence_level_annotation": datasets.Value("bool"),
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"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
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}),
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"image": datasets.Image(decode=False),
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})
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@@ -242,12 +744,13 @@ class LILA(datasets.GeneratorBasedBuilder):
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"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
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"seq_num_frames": datasets.Value("int32"),
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"original_relative_path": datasets.Value("string"),
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"datetime": datasets.Value("
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"location": datasets.Value("string"),
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"annotations": datasets.Sequence({
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"id": datasets.Value("string"),
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"category_id": datasets.Value("int32"),
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"sequence_level_annotation": datasets.Value("bool"),
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}),
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"image": datasets.Image(decode=False),
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})
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@@ -257,7 +760,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
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"width": datasets.Value("int32"), "height": datasets.Value("int32"),
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"seq_num_frames": datasets.Value("int32"),
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"datetime": datasets.Value("
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"corrupt": datasets.Value("bool"),
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"location": datasets.Value("string"),
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"annotations": datasets.Sequence({
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@@ -266,7 +769,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"sequence_level_annotation": datasets.Value("bool"),
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"seq_id": datasets.Value("string"),
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"season": datasets.Value("string"),
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"datetime": datasets.Value("
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"subject_id": datasets.Value("string"),
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"count": datasets.Value("string"),
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"standing": datasets.Value("float32"),
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@@ -275,6 +778,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"interacting": datasets.Value("float32"),
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"young_present": datasets.Value("float32"),
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"location": datasets.Value("string"),
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}),
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"bboxes": datasets.Sequence({
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"id": datasets.Value("string"),
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@@ -292,7 +796,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
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"width": datasets.Value("int32"), "height": datasets.Value("int32"),
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"seq_num_frames": datasets.Value("int32"),
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-
"datetime": datasets.Value("
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"corrupt": datasets.Value("bool"),
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"location": datasets.Value("string"),
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"annotations": datasets.Sequence({
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@@ -301,7 +805,7 @@ class LILA(datasets.GeneratorBasedBuilder):
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"sequence_level_annotation": datasets.Value("bool"),
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"seq_id": datasets.Value("string"),
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"season": datasets.Value("string"),
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"datetime": datasets.Value("
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"subject_id": datasets.Value("string"),
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"count": datasets.Value("string"),
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"standing": datasets.Value("float32"),
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@@ -310,6 +814,31 @@ class LILA(datasets.GeneratorBasedBuilder):
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"interacting": datasets.Value("float32"),
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"young_present": datasets.Value("float32"),
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"location": datasets.Value("string"),
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}),
|
| 314 |
"image": datasets.Image(decode=False),
|
| 315 |
})
|
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@@ -317,12 +846,13 @@ class LILA(datasets.GeneratorBasedBuilder):
|
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| 317 |
return datasets.Features({
|
| 318 |
"id": datasets.Value("string"), "file_name": datasets.Value("string"),
|
| 319 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 320 |
-
"seq_num_frames": datasets.Value("int32"), "datetime": datasets.Value("
|
| 321 |
"location": datasets.Value("string"),
|
| 322 |
"annotations": datasets.Sequence({
|
| 323 |
"id": datasets.Value("string"),
|
| 324 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 325 |
"category_id": datasets.Value("int32"),
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|
| 326 |
}),
|
| 327 |
"image": datasets.Image(decode=False),
|
| 328 |
})
|
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@@ -348,7 +878,7 @@ class LILA(datasets.GeneratorBasedBuilder):
|
|
| 348 |
|
| 349 |
def _split_generators(self, dl_manager):
|
| 350 |
archive_path = dl_manager.download_and_extract(self.config.metadata_url)
|
| 351 |
-
if archive_path.endswith(".zip"):
|
| 352 |
archive_path = os.path.join(archive_path, os.listdir(archive_path)[0])
|
| 353 |
|
| 354 |
return [
|
|
|
|
| 57 |
|
| 58 |
# How do I make these point to the particular commit ID?
|
| 59 |
_LILA_URLS = {
|
| 60 |
+
"Caltech Camera Traps": "Caltech_Camera_Traps.jsonl.zip",
|
| 61 |
+
"ENA24": "ENA24.jsonl.zip",
|
| 62 |
+
"Missouri Camera Traps": "Missouri_Camera_Traps.jsonl.zip",
|
| 63 |
"NACTI": "NACTI.jsonl.zip",
|
| 64 |
"WCS Camera Traps": "WCS_Camera_Traps.jsonl.zip",
|
| 65 |
"Wellington Camera Traps": "Wellington_Camera_Traps.jsonl.zip",
|
|
|
|
| 68 |
"Idaho Camera Traps": "Idaho_Camera_Traps.jsonl.zip",
|
| 69 |
"Snapshot Serengeti": "Snapshot_Serengeti.jsonl.zip",
|
| 70 |
"Snapshot Karoo": "Snapshot_Karoo.jsonl.zip",
|
| 71 |
+
"Snapshot Kgalagadi": "Snapshot_Kgalagadi.jsonl.zip",
|
| 72 |
"Snapshot Enonkishu": "Snapshot_Enonkishu.jsonl.zip",
|
| 73 |
"Snapshot Camdeboo": "Snapshot_Camdeboo.jsonl.zip",
|
| 74 |
"Snapshot Mountain Zebra": "Snapshot_Mountain_Zebra.jsonl.zip",
|
| 75 |
+
"Snapshot Kruger": "Snapshot_Kruger.jsonl.zip",
|
| 76 |
"SWG Camera Traps": "SWG_Camera_Traps.jsonl.zip",
|
| 77 |
"Orinoquia Camera Traps": "Orinoquia_Camera_Traps.jsonl.zip",
|
| 78 |
}
|
| 79 |
|
| 80 |
+
# TODO: Put these all in text files
|
| 81 |
+
_TAXONOMY = {
|
| 82 |
+
"kingdom": datasets.ClassLabel(num_classes=1, names=["animalia"]),
|
| 83 |
+
"phylum": datasets.ClassLabel(num_classes=2, names=["chordata", "arthropoda"]),
|
| 84 |
+
"subphylum": datasets.ClassLabel(num_classes=5, names=[
|
| 85 |
+
'vertebrata', 'hexapoda', 'crustacea', 'chelicerata',
|
| 86 |
+
'myriapoda'
|
| 87 |
+
]),
|
| 88 |
+
"superclass": datasets.ClassLabel(num_classes=1, names=["multicrustacea"]),
|
| 89 |
+
"class": datasets.ClassLabel(num_classes=8, names=[
|
| 90 |
+
'mammalia', 'aves', 'insecta', 'reptilia', 'malacostraca',
|
| 91 |
+
'arachnida', 'diplopoda', 'amphibia'
|
| 92 |
+
]),
|
| 93 |
+
"subclass": datasets.ClassLabel(num_classes=3, names=[
|
| 94 |
+
'theria', 'pterygota', 'eumalacostraca'
|
| 95 |
+
]),
|
| 96 |
+
"infraclass": datasets.ClassLabel(num_classes=2, names=[
|
| 97 |
+
'placentalia', 'marsupialia'
|
| 98 |
+
]),
|
| 99 |
+
"superorder": datasets.ClassLabel(num_classes=5, names=[
|
| 100 |
+
'laurasiatheria', 'euarchontoglires', 'eucarida', 'xenarthra',
|
| 101 |
+
'afrotheria'
|
| 102 |
+
]),
|
| 103 |
+
"order": datasets.ClassLabel(num_classes=53, names=[
|
| 104 |
+
'carnivora', 'chiroptera', 'artiodactyla', 'squamata',
|
| 105 |
+
'didelphimorphia', 'lagomorpha', 'rodentia', 'primates',
|
| 106 |
+
'passeriformes', 'galliformes', 'perissodactyla',
|
| 107 |
+
'accipitriformes', 'caprimulgiformes', 'lepidoptera',
|
| 108 |
+
'strigiformes', 'piciformes', 'falconiformes', 'charadriiformes',
|
| 109 |
+
'decapoda', 'columbiformes', 'pelecaniformes', 'procellariiformes',
|
| 110 |
+
'gruiformes', 'testudines', 'araneae', 'tinamiformes', 'cingulata',
|
| 111 |
+
'coraciiformes', 'hymenoptera', 'pilosa', 'cathartiformes',
|
| 112 |
+
'tubulidentata', 'otidiformes', 'struthioniformes', 'proboscidea',
|
| 113 |
+
'crocodylia', 'pholidota', 'scandentia', 'trogoniformes',
|
| 114 |
+
'bucerotiformes', 'anseriformes', 'eulipotyphla', 'psittaciformes',
|
| 115 |
+
'cuculiformes', 'ciconiiformes', 'musophagiformes', 'hyracoidea',
|
| 116 |
+
'eurypygiformes', 'afrosoricida', 'galbuliformes', 'macroscelidea',
|
| 117 |
+
'anura', 'rheiformes'
|
| 118 |
+
]),
|
| 119 |
+
"suborder": datasets.ClassLabel(num_classes=17, names=[
|
| 120 |
+
'ruminantia', 'suina', 'sciuromorpha', 'haplorhini',
|
| 121 |
+
'hystricomorpha', 'pleocyemata', 'sauria', 'myomorpha',
|
| 122 |
+
'castorimorpha', 'apocrita', 'vermilingua', 'anomaluromorpha',
|
| 123 |
+
'whippomorpha', 'serpentes', 'tylopoda', 'strepsirrhini',
|
| 124 |
+
'tenrecomorpha'
|
| 125 |
+
]),
|
| 126 |
+
"infraorder": datasets.ClassLabel(num_classes=9, names=[
|
| 127 |
+
'simiiformes', 'hystricognathi', 'brachyura', 'anomura',
|
| 128 |
+
'aculeata', 'ancodonta', 'chiromyiformes', 'lemuriformes',
|
| 129 |
+
'lorisiformes'
|
| 130 |
+
]),
|
| 131 |
+
"superfamily": datasets.ClassLabel(num_classes=12, names=[
|
| 132 |
+
'hominoidea', 'erethizontoidea', 'paguroidea', 'muroidea',
|
| 133 |
+
'chelonioidea', 'cavioidea', 'formicoidea', 'octodontoidea',
|
| 134 |
+
'lemuroidea', 'chinchilloidea', 'cheirogaleoidea', 'papilionoidea'
|
| 135 |
+
]),
|
| 136 |
+
"family": datasets.ClassLabel(num_classes=159, names=[
|
| 137 |
+
'mustelidae', 'felidae', 'bovidae', 'canidae', 'cervidae',
|
| 138 |
+
'didelphidae', 'suidae', 'leporidae', 'procyonidae', 'mephitidae',
|
| 139 |
+
'sciuridae', 'hominidae', 'ursidae', 'corvidae', 'phasianidae',
|
| 140 |
+
'equidae', 'turdidae', 'accipitridae', 'trochilidae',
|
| 141 |
+
'erethizontidae', 'antilocapridae', 'sittidae', 'parulidae',
|
| 142 |
+
'cardinalidae', 'picidae', 'falconidae', 'strigidae', 'laridae',
|
| 143 |
+
'columbidae', 'ardeidae', 'calcinidae', 'iguanidae',
|
| 144 |
+
'megapodiidae', 'mimidae', 'varanidae', 'procellariidae',
|
| 145 |
+
'rallidae', 'muridae', 'phocidae', 'hydrobatidae', 'dasyproctidae',
|
| 146 |
+
'tayassuidae', 'tinamidae', 'cuniculidae', 'odontophoridae',
|
| 147 |
+
'dasypodidae', 'passerellidae', 'troglodytidae', 'cricetidae',
|
| 148 |
+
'geomyidae', 'momotidae', 'formicidae', 'caviidae', 'cracidae',
|
| 149 |
+
'myrmecophagidae', 'chlamyphoridae', 'tapiridae', 'cebidae',
|
| 150 |
+
'pitheciidae', 'cathartidae', 'atelidae', 'caprimulgidae',
|
| 151 |
+
'orycteropodidae', 'hyaenidae', 'cercopithecidae', 'otididae',
|
| 152 |
+
'gruidae', 'viverridae', 'pedetidae', 'herpestidae',
|
| 153 |
+
'struthionidae', 'hystricidae', 'sagittariidae', 'testudinidae',
|
| 154 |
+
'elephantidae', 'giraffidae', 'hippopotamidae', 'rhinocerotidae',
|
| 155 |
+
'crocodylidae', 'numididae', 'manidae', 'irenidae', 'echimyidae',
|
| 156 |
+
'pittidae', 'leiothrichidae', 'muscicapidae', 'tragulidae',
|
| 157 |
+
'scolopacidae', 'hylobatidae', 'timaliidae', 'stenostiridae',
|
| 158 |
+
'tupaiidae', 'trogonidae', 'bucerotidae', 'prionodontidae',
|
| 159 |
+
'acrocephalidae', 'pycnonotidae', 'anatidae', 'anhimidae',
|
| 160 |
+
'anomaluridae', 'aramidae', 'erinaceidae', 'brachypteraciidae',
|
| 161 |
+
'threskiornithidae', 'psittacidae', 'buphagidae', 'burhinidae',
|
| 162 |
+
'camelidae', 'sarothruridae', 'cuculidae', 'ciconiidae',
|
| 163 |
+
'furnariidae', 'cisticolidae', 'apodidae', 'musophagidae',
|
| 164 |
+
'nesomyidae', 'eupleridae', 'daubentoniidae', 'procaviidae',
|
| 165 |
+
'dicaeidae', 'dicruridae', 'lemuridae', 'laniidae', 'vangidae',
|
| 166 |
+
'eurypygidae', 'formicariidae', 'galagidae', 'grallariidae',
|
| 167 |
+
'charadriidae', 'tenrecidae', 'scotocercidae', 'chinchillidae',
|
| 168 |
+
'sturnidae', 'malaconotidae', 'macrosphenidae', 'cheirogaleidae',
|
| 169 |
+
'alaudidae', 'icteridae', 'bucconidae', 'motacillidae',
|
| 170 |
+
'nandiniidae', 'nectariniidae', 'estrildidae', 'bernieridae',
|
| 171 |
+
'alligatoridae', 'macroscelididae', 'ploceidae', 'indriidae',
|
| 172 |
+
'psophiidae', 'ramphastidae', 'ranidae', 'rheidae', 'spalacidae',
|
| 173 |
+
'scincidae', 'soricidae', 'monarchidae', 'thryonomyidae',
|
| 174 |
+
'teiidae', 'tytonidae'
|
| 175 |
+
]),
|
| 176 |
+
"subfamily": datasets.ClassLabel(num_classes=69, names=[
|
| 177 |
+
'taxidiinae', 'felinae', 'bovinae', 'capreolinae',
|
| 178 |
+
'didelphinae', 'suinae', 'sciurinae', 'homininae', 'ursinae',
|
| 179 |
+
'xerinae', 'mephitinae', 'antilopinae', 'cervinae', 'mustelinae',
|
| 180 |
+
'guloninae', 'erethizontinae', 'sterninae', 'ardeinae', 'murinae',
|
| 181 |
+
'lutrinae', 'melinae', 'neotominae', 'hydrochoerinae',
|
| 182 |
+
'tigriornithinae', 'tolypeutinae', 'pantherinae', 'cebinae',
|
| 183 |
+
'callicebinae', 'alouattinae', 'saimiriinae', 'protelinae',
|
| 184 |
+
'cercopithecinae', 'genettinae', 'mungotinae', 'herpestinae',
|
| 185 |
+
'ictonychinae', 'hyaeninae', 'mellivorinae', 'echimyinae',
|
| 186 |
+
'paradoxurinae', 'ratufinae', 'helictidinae', 'colobinae',
|
| 187 |
+
'viverrinae', 'hemigalinae', 'callosciurinae', 'erinaceinae',
|
| 188 |
+
'atelinae', 'camelinae', 'caviinae', 'furnariinae', 'criniferinae',
|
| 189 |
+
'cricetomyinae', 'euplerinae', 'deomyinae', 'nesomyinae',
|
| 190 |
+
'euphractinae', 'galidiinae', 'tenrecinae', 'oryzorictinae',
|
| 191 |
+
'musophaginae', 'myadinae', 'macroscelidinae', 'rhizomyinae',
|
| 192 |
+
'rhynchocyoninae', 'scincinae', 'crocidurinae', 'tremarctinae',
|
| 193 |
+
'tupinambinae'
|
| 194 |
+
]),
|
| 195 |
+
"tribe": datasets.ClassLabel(num_classes=46, names=[
|
| 196 |
+
'bovini', 'odocoileini', 'didelphini', 'suini', 'sciurini',
|
| 197 |
+
'tamiini', 'marmotini', 'caprini', 'cervini', 'alceini', 'rattini',
|
| 198 |
+
'capreolini', 'apodemini', 'reithrodontomyini', 'neotomini',
|
| 199 |
+
'papionini', 'alcelaphini', 'potamochoerini', 'cephalophini',
|
| 200 |
+
'tragelaphini', 'hippotragini', 'oreotragini', 'cercopithecini',
|
| 201 |
+
'reduncini', 'antilopini', 'aepycerotini', 'phacochoerini',
|
| 202 |
+
'xerini', 'echimyini', 'pteromyini', 'presbytini', 'muntiacini',
|
| 203 |
+
'callosciurini', 'camelini', 'colobini', 'praomyini',
|
| 204 |
+
'protoxerini', 'arvicanthini', 'malacomyini', 'metachirini',
|
| 205 |
+
'murini', 'neotragini', 'macroscelidini', 'myocastorini',
|
| 206 |
+
'rhizomyini', 'lamini'
|
| 207 |
+
]),
|
| 208 |
+
"genus": datasets.ClassLabel(num_classes=476, names=[
|
| 209 |
+
'taxidea', 'lynx', 'felis', 'bos', 'canis', 'odocoileus',
|
| 210 |
+
'urocyon', 'puma', 'didelphis', 'sus', 'procyon', 'sciurus',
|
| 211 |
+
'homo', 'ursus', 'corvus', 'gallus', 'tamias', 'sylvilagus',
|
| 212 |
+
'equus', 'vulpes', 'mephitis', 'meleagris', 'marmota', 'ovis',
|
| 213 |
+
'sialia', 'nucifraga', 'cervus', 'mustela', 'pekania', 'neogale',
|
| 214 |
+
'pica', 'alces', 'erethizon', 'antilocapra', 'sitta', 'ixoreus',
|
| 215 |
+
'piranga', 'falco', 'strix', 'anous', 'athene', 'nasua', 'capra',
|
| 216 |
+
'ardea', 'butorides', 'calcinus', 'iguana', 'caloenas', 'rattus',
|
| 217 |
+
'calonectris', 'asio', 'hydrobates', 'zenaida', 'nyctanassa',
|
| 218 |
+
'turdus', 'dasyprocta', 'pecari', 'lepus', 'tinamus', 'leopardus',
|
| 219 |
+
'cuniculus', 'mazama', 'tamiasciurus', 'capreolus', 'apodemus',
|
| 220 |
+
'callipepla', 'cyanocitta', 'dasypus', 'dendragapus', 'junco',
|
| 221 |
+
'lontra', 'martes', 'meles', 'otospermophilus', 'perisoreus',
|
| 222 |
+
'troglodytes', 'peromyscus', 'neotoma', 'momotus', 'speothos',
|
| 223 |
+
'hydrochoerus', 'cerdocyon', 'mitu', 'tigrisoma', 'myrmecophaga',
|
| 224 |
+
'priodontes', 'pteronura', 'panthera', 'herpailurus', 'tapirus',
|
| 225 |
+
'sapajus', 'plecturocebus', 'tamandua', 'penelope', 'eira',
|
| 226 |
+
'cathartes', 'alouatta', 'saimiri', 'tayassu', 'orycteropus',
|
| 227 |
+
'proteles', 'papio', 'damaliscus', 'syncerus', 'potamochoerus',
|
| 228 |
+
'ardeotis', 'caracal', 'anthropoides', 'sylvicapra', 'tragelaphus',
|
| 229 |
+
'dama', 'otocyon', 'oryx', 'genetta', 'pedetes', 'alcelaphus',
|
| 230 |
+
'lupulella', 'oreotragus', 'suricata', 'herpestes', 'cynictis',
|
| 231 |
+
'chlorocebus', 'struthio', 'hystrix', 'redunca', 'pelea',
|
| 232 |
+
'sagittarius', 'antidorcas', 'raphicerus', 'connochaetes',
|
| 233 |
+
'ictonyx', 'acinonyx', 'madoqua', 'cephalophus', 'loxodonta',
|
| 234 |
+
'nanger', 'eudorcas', 'giraffa', 'hippopotamus', 'crocuta',
|
| 235 |
+
'aepyceros', 'ourebia', 'phacochoerus', 'kobus', 'neotis',
|
| 236 |
+
'parahyaena', 'bunolagus', 'diceros', 'mellivora', 'crocodylus',
|
| 237 |
+
'pronolagus', 'hippotragus', 'leptailurus', 'lycaon', 'xerus',
|
| 238 |
+
'ceratotherium', 'hyaena', 'nesolagus', 'irena', 'atherurus',
|
| 239 |
+
'macaca', 'dactylomys', 'hydrornis', 'macropygia', 'varanus',
|
| 240 |
+
'arctictis', 'ratufa', 'pterorhinus', 'cinclidium', 'myophonus',
|
| 241 |
+
'moschiola', 'capricornis', 'cissa', 'paradoxurus', 'urva',
|
| 242 |
+
'rheinardia', 'spilornis', 'chalcophaps', 'scolopax', 'melogale',
|
| 243 |
+
'enicurus', 'trachypithecus', 'petaurista', 'cyanoderma',
|
| 244 |
+
'catopuma', 'garrulax', 'culicicapa', 'polyplectron', 'arctonyx',
|
| 245 |
+
'muntiacus', 'viverra', 'erythrogenys', 'prionailurus', 'picus',
|
| 246 |
+
'pardofelis', 'paguma', 'nisaetus', 'ducula', 'tupaia',
|
| 247 |
+
'harpactes', 'geokichla', 'chrotogale', 'callosciurus', 'manis',
|
| 248 |
+
'dremomys', 'pygathrix', 'trochalopteron', 'ianthocincla',
|
| 249 |
+
'aceros', 'rusa', 'zoothera', 'leiothrix', 'lophura', 'prionodon',
|
| 250 |
+
'helarctos', 'pitta', 'tamiops', 'myiomela', 'urocissa',
|
| 251 |
+
'accipiter', 'acrocephalus', 'acryllium', 'agamia', 'alectoris',
|
| 252 |
+
'chamaetylas', 'alophoixus', 'alopochen', 'stelgidillas',
|
| 253 |
+
'eurillas', 'anhima', 'anomalurus', 'aonyx', 'aquila', 'aramides',
|
| 254 |
+
'aramus', 'arborophila', 'arctogalidia', 'ardeola', 'argusianus',
|
| 255 |
+
'arremonops', 'atelerix', 'ateles', 'atelocynus', 'atelornis',
|
| 256 |
+
'atilax', 'balearica', 'bambusicola', 'baryphthengus', 'bdeogale',
|
| 257 |
+
'blastocerus', 'bostrychia', 'brachypteracias', 'brotogeris',
|
| 258 |
+
'bubo', 'bubulcus', 'buphagus', 'burhinus', 'butastur', 'buteo',
|
| 259 |
+
'buteogallus', 'bycanistes', 'cabassous', 'cairina', 'caloperdix',
|
| 260 |
+
'camelus', 'mentocrex', 'caprimulgus', 'caracara', 'carpococcyx',
|
| 261 |
+
'hylocichla', 'catharus', 'cavia', 'cebus', 'cercocebus',
|
| 262 |
+
'cercopithecus', 'allochrocebus', 'cercotrichas', 'ortalis',
|
| 263 |
+
'chelonoidis', 'ciconia', 'cinclodes', 'circus', 'cisticola',
|
| 264 |
+
'civettictis', 'claravis', 'cochlearius', 'coendou', 'collocalia',
|
| 265 |
+
'colobus', 'colomys', 'columba', 'columbina', 'conepatus',
|
| 266 |
+
'copsychus', 'coragyps', 'corythaixoides', 'cossypha', 'coturnix',
|
| 267 |
+
'coua', 'crax', 'cricetomys', 'cryptoprocta', 'crypturellus',
|
| 268 |
+
'cuon', 'cyanoptila', 'cyornis', 'daptrius', 'daubentonia',
|
| 269 |
+
'dendrocitta', 'dendrohyrax', 'ortygornis', 'deomys', 'dicaeum',
|
| 270 |
+
'dicerorhinus', 'dicrurus', 'melaenornis', 'egretta', 'elephas',
|
| 271 |
+
'eliurus', 'larvivora', 'erythrocebus', 'eulemur', 'euphractus',
|
| 272 |
+
'eupleres', 'eupodotis', 'eurocephalus', 'euryceros', 'eurypyga',
|
| 273 |
+
'eutriorchis', 'ficedula', 'formicarius', 'fossa', 'scleroptila',
|
| 274 |
+
'pternistis', 'francolinus', 'funisciurus', 'galago', 'galictis',
|
| 275 |
+
'galidia', 'galidictis', 'geotrygon', 'grallaria', 'guttera',
|
| 276 |
+
'haliaeetus', 'vanellus', 'harpia', 'heliosciurus', 'helogale',
|
| 277 |
+
'hemicentetes', 'hemigalus', 'urosphena', 'heterohyrax',
|
| 278 |
+
'hippocamelus', 'hybomys', 'hylomyscus', 'hylopetes', 'hypogeomys',
|
| 279 |
+
'ichneumia', 'arundinax', 'jynx', 'lagidium', 'lamprotornis',
|
| 280 |
+
'laniarius', 'lanius', 'lariscus', 'lemur', 'leptotila',
|
| 281 |
+
'lissotis', 'litocranius', 'lophotibis', 'lutreolina', 'lycalopex',
|
| 282 |
+
'malacomys', 'melierax', 'melocichla', 'mesembrinibis',
|
| 283 |
+
'chloropicus', 'metachirus', 'micrastur', 'microcebus',
|
| 284 |
+
'microgale', 'microsciurus', 'mirafra', 'molothrus', 'monasa',
|
| 285 |
+
'morphnus', 'motacilla', 'mungos', 'mus', 'musophaga', 'mydaus',
|
| 286 |
+
'myoprocta', 'mystacornis', 'nandinia', 'cyanomitra', 'oressochen',
|
| 287 |
+
'neocossyphus', 'neofelis', 'neomorphus', 'delacourella',
|
| 288 |
+
'streptopelia', 'nesomys', 'nesotragus', 'niltava', 'nothocrax',
|
| 289 |
+
'numida', 'nyctidromus', 'odontophorus', 'oenomys', 'oenanthe',
|
| 290 |
+
'otolemur', 'otus', 'oxylabes', 'paleosuchus', 'pan', 'paraxerus',
|
| 291 |
+
'pernis', 'petrodromus', 'phaethornis', 'philander', 'philantomba',
|
| 292 |
+
'pilherodius', 'xanthomixis', 'pipile', 'ploceus', 'poecilogale',
|
| 293 |
+
'pogonocichla', 'potos', 'praomys', 'presbytis', 'procavia',
|
| 294 |
+
'piliocolobus', 'proechimys', 'propithecus', 'protoxerus',
|
| 295 |
+
'psophia', 'pteroglossus', 'ramphastos', 'rana', 'rhea',
|
| 296 |
+
'rhizomys', 'rhynchocyon', 'rollulus', 'rupornis', 'ruwenzorornis',
|
| 297 |
+
'salanoia', 'saxicola', 'setifer', 'sheppardia', 'plestiodon',
|
| 298 |
+
'spilogale', 'spizaetus', 'stephanoaetus', 'stigmochelys',
|
| 299 |
+
'amazona', 'suncus', 'sundasciurus', 'tauraco', 'tenrec',
|
| 300 |
+
'terpsiphone', 'thamnomys', 'thryonomys', 'tockus', 'tolypeutes',
|
| 301 |
+
'tragulus', 'tremarctos', 'trichys', 'tupinambis', 'turtur',
|
| 302 |
+
'tyto', 'vicugna', 'viverricula', 'xenoperdix', 'euxerus',
|
| 303 |
+
'zonotrichia', 'erinaceus'
|
| 304 |
+
]),
|
| 305 |
+
"species": datasets.ClassLabel(num_classes=668, names=[
|
| 306 |
+
'taxidea taxus', 'lynx rufus', 'felis catus', 'bos taurus',
|
| 307 |
+
'canis latrans', 'canis familiaris', 'urocyon cinereoargenteus',
|
| 308 |
+
'puma concolor', 'didelphis virginiana', 'sus scrofa',
|
| 309 |
+
'procyon lotor', 'urocyon littoralis', 'homo sapiens',
|
| 310 |
+
'ursus americanus', 'corvus brachyrhynchos', 'gallus gallus',
|
| 311 |
+
'tamias striatus', 'sylvilagus floridanus', 'sciurus niger',
|
| 312 |
+
'sciurus carolinensis', 'equus caballus', 'vulpes vulpes',
|
| 313 |
+
'mephitis mephitis', 'odocoileus virginianus',
|
| 314 |
+
'meleagris gallopavo', 'marmota monax', 'ovis canadensis',
|
| 315 |
+
'nucifraga columbiana', 'cervus canadensis', 'mustela erminea',
|
| 316 |
+
'pekania pennanti', 'neogale frenata', 'pica hudsonia',
|
| 317 |
+
'alces alces', 'erethizon dorsatum', 'antilocapra americana',
|
| 318 |
+
'corvus corax', 'sitta canadensis', 'ixoreus naevius',
|
| 319 |
+
'piranga ludoviciana', 'canis lupus', 'falco sparverius',
|
| 320 |
+
'strix varia', 'anous stolidus', 'athene cunicularia',
|
| 321 |
+
'nasua nasua', 'equus asinus', 'capra hircus', 'ardea herodias',
|
| 322 |
+
'butorides virescens', 'calcinus tubularis', 'falco tinnunculus',
|
| 323 |
+
'caloenas nicobarica', 'asio flammeus', 'hydrobates pelagicus',
|
| 324 |
+
'zenaida asiatica', 'nyctanassa violacea', 'dasyprocta coibae',
|
| 325 |
+
'pecari tajacu', 'didelphis marsupialis', 'lepus europaeus',
|
| 326 |
+
'tinamus major', 'ovis ammon', 'leopardus pardalis',
|
| 327 |
+
'mazama americana', 'cervus elaphus', 'tamiasciurus hudsonicus',
|
| 328 |
+
'rattus praetor', 'nasua narica', 'apodemus sylvaticus',
|
| 329 |
+
'callipepla californica', 'cyanocitta stelleri',
|
| 330 |
+
'dasypus novemcinctus', 'dendragapus obscurus', 'equus africanus',
|
| 331 |
+
'equus ferus', 'junco hyemalis', 'lepus americanus',
|
| 332 |
+
'lepus californicus', 'lontra canadensis', 'marmota flaviventris',
|
| 333 |
+
'martes americana', 'meles meles', 'odocoileus hemionus',
|
| 334 |
+
'otospermophilus beecheyi', 'perisoreus canadensis',
|
| 335 |
+
'rattus rattus', 'troglodytes aedon', 'zenaida macroura',
|
| 336 |
+
'momotus momota', 'dasyprocta fuliginosa', 'speothos venaticus',
|
| 337 |
+
'hydrochoerus hydrochaeris', 'iguana iguana', 'cerdocyon thous',
|
| 338 |
+
'mitu tomentosum', 'tigrisoma fasciatum',
|
| 339 |
+
'myrmecophaga tridactyla', 'priodontes maximus',
|
| 340 |
+
'pteronura brasiliensis', 'panthera onca',
|
| 341 |
+
'herpailurus yagouaroundi', 'tapirus terrestris', 'sapajus apella',
|
| 342 |
+
'leopardus wiedii', 'lontra longicaudis', 'sciurus igniventris',
|
| 343 |
+
'dasyprocta guamara', 'plecturocebus ornatus', 'mitu salvini',
|
| 344 |
+
'tamandua tetradactyla', 'penelope jacquacu', 'cuniculus paca',
|
| 345 |
+
'eira barbara', 'cathartes aura', 'penelope jacucaca',
|
| 346 |
+
'tayassu pecari', 'orycteropus afer', 'proteles cristatus',
|
| 347 |
+
'damaliscus pygargus', 'syncerus caffer', 'potamochoerus larvatus',
|
| 348 |
+
'ardeotis kori', 'caracal caracal', 'anthropoides paradiseus',
|
| 349 |
+
'sylvicapra grimmia', 'tragelaphus oryx', 'dama dama',
|
| 350 |
+
'otocyon megalotis', 'oryx gazella', 'lepus saxatilis',
|
| 351 |
+
'pedetes capensis', 'alcelaphus buselaphus', 'lupulella mesomelas',
|
| 352 |
+
'oreotragus oreotragus', 'tragelaphus strepsiceros',
|
| 353 |
+
'suricata suricatta', 'herpestes ichneumon',
|
| 354 |
+
'cynictis penicillata', 'chlorocebus pygerythrus',
|
| 355 |
+
'struthio camelus', 'hystrix africaeaustralis',
|
| 356 |
+
'redunca fulvorufula', 'pelea capreolus',
|
| 357 |
+
'sagittarius serpentarius', 'antidorcas marsupialis',
|
| 358 |
+
'raphicerus campestris', 'connochaetes gnou', 'equus zebra',
|
| 359 |
+
'ictonyx striatus', 'tragelaphus scriptus', 'acinonyx jubatus',
|
| 360 |
+
'loxodonta africana', 'nanger granti', 'eudorcas thomsonii',
|
| 361 |
+
'giraffa camelopardalis', 'lepus victoriae',
|
| 362 |
+
'hippopotamus amphibius', 'crocuta crocuta', 'aepyceros melampus',
|
| 363 |
+
'panthera pardus', 'panthera leo', 'ourebia ourebi',
|
| 364 |
+
'hystrix cristata', 'damaliscus lunatus', 'phacochoerus africanus',
|
| 365 |
+
'kobus ellipsiprymnus', 'connochaetes taurinus', 'equus quagga',
|
| 366 |
+
'neotis ludwigii', 'vulpes chama', 'parahyaena brunnea',
|
| 367 |
+
'herpestes pulverulentus', 'bunolagus monticularis',
|
| 368 |
+
'diceros bicornis', 'felis lybica', 'lepus capensis',
|
| 369 |
+
'mellivora capensis', 'crocodylus niloticus',
|
| 370 |
+
'cephalophus natalensis', 'lupulella adusta',
|
| 371 |
+
'tragelaphus angasii', 'pronolagus randensis',
|
| 372 |
+
'hippotragus equinus', 'leptailurus serval', 'lycaon pictus',
|
| 373 |
+
'ceratotherium simum', 'hyaena hyaena', 'nesolagus timminsi',
|
| 374 |
+
'irena puella', 'ursus thibetanus', 'atherurus macrourus',
|
| 375 |
+
'mustela strigidorsa', 'hydrornis elliotii', 'macropygia unchall',
|
| 376 |
+
'varanus bengalensis', 'arctictis binturong', 'ratufa bicolor',
|
| 377 |
+
'pterorhinus chinensis', 'cinclidium frontale',
|
| 378 |
+
'hydrornis cyaneus', 'myophonus caeruleus', 'strix leptogrammica',
|
| 379 |
+
'moschiola meminna', 'capricornis sumatraensis', 'cissa chinensis',
|
| 380 |
+
'paradoxurus hermaphroditus', 'urva urva', 'rheinardia ocellata',
|
| 381 |
+
'spilornis cheela', 'chalcophaps indica', 'scolopax rusticola',
|
| 382 |
+
'turdus obscurus', 'trachypithecus francoisi',
|
| 383 |
+
'cyanoderma chrysaeum', 'catopuma temminckii', 'garrulax maesi',
|
| 384 |
+
'culicicapa ceylonensis', 'polyplectron bicalcaratum',
|
| 385 |
+
'trachypithecus hatinhensis', 'arctonyx collaris',
|
| 386 |
+
'cissa hypoleuca', 'turdus cardis', 'muntiacus vuquangensis',
|
| 387 |
+
'viverra zibetha', 'erythrogenys hypoleucos',
|
| 388 |
+
'prionailurus bengalensis', 'picus chlorolophus',
|
| 389 |
+
'hystrix brachyura', 'pardofelis marmorata', 'paguma larvata',
|
| 390 |
+
'nisaetus nipalensis', 'ducula badia', 'pterorhinus pectoralis',
|
| 391 |
+
'tupaia belangeri', 'harpactes oreskios', 'geokichla citrina',
|
| 392 |
+
'chrotogale owstoni', 'callosciurus erythraeus',
|
| 393 |
+
'trachypithecus phayrei', 'macaca nemestrina',
|
| 394 |
+
'dremomys rufigenis', 'picus rabieri', 'muntiacus muntjak',
|
| 395 |
+
'pygathrix nemaeus', 'trochalopteron milnei',
|
| 396 |
+
'muntiacus rooseveltorum', 'garrulax castanotis',
|
| 397 |
+
'ianthocincla konkakinhensis', 'aceros nipalensis',
|
| 398 |
+
'rusa unicolor', 'zoothera dauma', 'geokichla sibirica',
|
| 399 |
+
'leiothrix argentauris', 'lophura nycthemera',
|
| 400 |
+
'prionodon pardicolor', 'butorides striata', 'macaca arctoides',
|
| 401 |
+
'helarctos malayanus', 'enicurus leschenaulti', 'myiomela leucura',
|
| 402 |
+
'urocissa whiteheadi', 'mustela kathiah', 'martes flavigula',
|
| 403 |
+
'accipiter madagascariensis', 'accipiter melanoleucus',
|
| 404 |
+
'acrocephalus baeticatus', 'acryllium vulturinum', 'agamia agami',
|
| 405 |
+
'alectoris rufa', 'chamaetylas poliophrys', 'alophoixus bres',
|
| 406 |
+
'alopochen aegyptiaca', 'alouatta sara',
|
| 407 |
+
'stelgidillas gracilirostris', 'eurillas latirostris',
|
| 408 |
+
'eurillas virens', 'anhima cornuta', 'anomalurus derbianus',
|
| 409 |
+
'aonyx cinereus', 'aquila heliaca', 'aquila rapax',
|
| 410 |
+
'aramides cajaneus', 'aramus guarauna',
|
| 411 |
+
'arborophila brunneopectus', 'arborophila rubrirostris',
|
| 412 |
+
'arborophila rufogularis', 'arctogalidia trivirgata',
|
| 413 |
+
'arctonyx hoevenii', 'ardea alba', 'ardea cocoi',
|
| 414 |
+
'ardea melanocephala', 'ardeola grayii', 'argusianus argus',
|
| 415 |
+
'arremonops chloronotus', 'asio madagascariensis',
|
| 416 |
+
'atelerix albiventris', 'ateles chamek', 'atelocynus microtis',
|
| 417 |
+
'atelornis pittoides', 'atherurus africanus', 'atilax paludinosus',
|
| 418 |
+
'balearica regulorum', 'bambusicola fytchii',
|
| 419 |
+
'baryphthengus martii', 'bdeogale crassicauda',
|
| 420 |
+
'bdeogale jacksoni', 'blastocerus dichotomus', 'bos gaurus',
|
| 421 |
+
'bostrychia hagedash', 'brachypteracias squamiger',
|
| 422 |
+
'bubulcus ibis', 'burhinus capensis', 'butastur indicus',
|
| 423 |
+
'buteo ridgwayi', 'buteogallus urubitinga', 'bycanistes brevis',
|
| 424 |
+
'cabassous centralis', 'cabassous unicinctus', 'cairina moschata',
|
| 425 |
+
'callosciurus notatus', 'caloperdix oculeus',
|
| 426 |
+
'camelus dromedarius', 'mentocrex kioloides', 'capra aegagrus',
|
| 427 |
+
'caracara plancus', 'carpococcyx renauldi',
|
| 428 |
+
'cathartes burrovianus', 'cathartes melambrotus',
|
| 429 |
+
'hylocichla mustelina', 'catharus ustulatus', 'cavia aperea',
|
| 430 |
+
'cebus albifrons', 'cephalophus harveyi', 'cephalophus nigrifrons',
|
| 431 |
+
'cephalophus silvicultor', 'cephalophus spadix',
|
| 432 |
+
'cercocebus sanjei', 'cercopithecus erythrogaster',
|
| 433 |
+
'allochrocebus lhoesti', 'cercopithecus mitis', 'ortalis vetula',
|
| 434 |
+
'chelonoidis carbonarius', 'ciconia maguari',
|
| 435 |
+
'cinclodes atacamensis', 'cinclodes fuscus', 'circus cyaneus',
|
| 436 |
+
'cisticola cherina', 'civettictis civetta', 'claravis pretiosa',
|
| 437 |
+
'cochlearius cochlearius', 'coendou bicolor', 'collocalia linchi',
|
| 438 |
+
'colobus angolensis', 'colomys goslingi', 'columba arquatrix',
|
| 439 |
+
'columba larvata', 'columbina talpacoti', 'conepatus chinga',
|
| 440 |
+
'conepatus semistriatus', 'copsychus albospecularis',
|
| 441 |
+
'copsychus malabaricus', 'copsychus saularis', 'coragyps atratus',
|
| 442 |
+
'corythaixoides leucogaster', 'cossypha archeri',
|
| 443 |
+
'coturnix delegorguei', 'coua caerulea', 'coua ruficeps',
|
| 444 |
+
'coua serriana', 'crax alector', 'crax rubra',
|
| 445 |
+
'cricetomys gambianus', 'cryptoprocta ferox',
|
| 446 |
+
'crypturellus atrocapillus', 'crypturellus boucardi',
|
| 447 |
+
'crypturellus cinereus', 'crypturellus cinnamomeus',
|
| 448 |
+
'crypturellus erythropus', 'crypturellus bartletti',
|
| 449 |
+
'crypturellus soui', 'crypturellus undulatus',
|
| 450 |
+
'crypturellus variegatus', 'cuniculus taczanowskii',
|
| 451 |
+
'cuon alpinus', 'cyanoptila cyanomelana', 'cyornis banyumas',
|
| 452 |
+
'daptrius ater', 'dasyprocta punctata', 'dasyprocta leporina',
|
| 453 |
+
'dasypus kappleri', 'daubentonia madagascariensis',
|
| 454 |
+
'dendrocitta occipitalis', 'dendrohyrax arboreus',
|
| 455 |
+
'ortygornis sephaena', 'deomys ferrugineus',
|
| 456 |
+
'dicaeum trigonostigma', 'dicerorhinus sumatrensis',
|
| 457 |
+
'dicrurus adsimilis', 'didelphis imperfecta', 'didelphis pernigra',
|
| 458 |
+
'melaenornis fischeri', 'egretta thula', 'elephas maximus',
|
| 459 |
+
'eliurus penicillatus', 'eliurus petteri', 'eliurus webbi',
|
| 460 |
+
'enicurus schistaceus', 'equus grevyi', 'larvivora cyane',
|
| 461 |
+
'erythrocebus patas', 'eudorcas rufifrons', 'eulemur albifrons',
|
| 462 |
+
'euphractus sexcinctus', 'eupleres goudotii',
|
| 463 |
+
'eupodotis senegalensis', 'eurocephalus ruppelli',
|
| 464 |
+
'euryceros prevostii', 'eurypyga helias', 'eutriorchis astur',
|
| 465 |
+
'felis chaus', 'felis silvestris', 'ficedula mugimaki',
|
| 466 |
+
'ficedula tricolor', 'formicarius analis', 'formicarius colma',
|
| 467 |
+
'fossa fossana', 'scleroptila afra', 'pternistis nobilis',
|
| 468 |
+
'funisciurus carruthersi', 'funisciurus pyrropus',
|
| 469 |
+
'galago senegalensis', 'galictis vittata', 'galidia elegans',
|
| 470 |
+
'galidictis fasciata', 'genetta genetta', 'genetta maculata',
|
| 471 |
+
'genetta servalina', 'genetta tigrina', 'geokichla gurneyi',
|
| 472 |
+
'geotrygon montana', 'geotrygon saphirina', 'grallaria andicolus',
|
| 473 |
+
'guttera pucherani', 'haliaeetus vociferoides', 'vanellus cayanus',
|
| 474 |
+
'harpia harpyja', 'buteogallus solitarius',
|
| 475 |
+
'heliosciurus rufobrachium', 'heliosciurus ruwenzorii',
|
| 476 |
+
'helogale parvula', 'hemicentetes semispinosus',
|
| 477 |
+
'hemigalus derbyanus', 'urosphena neumanni',
|
| 478 |
+
'herpestes sanguineus', 'urva semitorquata', 'heterohyrax brucei',
|
| 479 |
+
'hippocamelus antisensis', 'hybomys univittatus',
|
| 480 |
+
'hydrornis oatesi', 'hylomyscus stella', 'hylopetes alboniger',
|
| 481 |
+
'hypogeomys antimena', 'ichneumia albicauda', 'arundinax aedon',
|
| 482 |
+
'jynx torquilla', 'lagidium viscacia', 'lamprotornis chalybaeus',
|
| 483 |
+
'lamprotornis hildebrandti', 'lamprotornis superbus',
|
| 484 |
+
'laniarius funebris', 'lanius collaris', 'lariscus insignis',
|
| 485 |
+
'leopardus tigrinus', 'leptotila plumbeiceps',
|
| 486 |
+
'leptotila rufaxilla', 'leptotila verreauxi',
|
| 487 |
+
'lissotis hartlaubii', 'lissotis melanogaster',
|
| 488 |
+
'litocranius walleri', 'lophotibis cristata', 'eupodotis gindiana',
|
| 489 |
+
'lophura diardi', 'lophura erythrophthalma', 'lophura ignita',
|
| 490 |
+
'lophura inornata', 'lutreolina crassicaudata',
|
| 491 |
+
'lycalopex culpaeus', 'macaca assamensis', 'macaca fascicularis',
|
| 492 |
+
'macaca mulatta', 'madoqua guentheri', 'malacomys longipes',
|
| 493 |
+
'manis javanica', 'mazama temama', 'mazama chunyi',
|
| 494 |
+
'mazama gouazoubira', 'odocoileus pandora',
|
| 495 |
+
'melaenornis ardesiacus', 'melaenornis pammelaina',
|
| 496 |
+
'meleagris ocellata', 'melierax poliopterus',
|
| 497 |
+
'melocichla mentalis', 'melogale everetti', 'melogale personata',
|
| 498 |
+
'mesembrinibis cayennensis', 'chloropicus griseocephalus',
|
| 499 |
+
'metachirus nudicaudatus', 'microcebus murinus',
|
| 500 |
+
'microsciurus flaviventer', 'microsciurus mimulus',
|
| 501 |
+
'mitu tuberosum', 'molothrus oryzivorus', 'monasa morphoeus',
|
| 502 |
+
'morphnus guianensis', 'motacilla flava', 'motacilla flaviventris',
|
| 503 |
+
'mungos mungo', 'mus minutoides', 'musophaga rossae',
|
| 504 |
+
'mustela lutreolina', 'mydaus javanensis', 'myophonus glaucinus',
|
| 505 |
+
'myophonus melanurus', 'myoprocta pratti', 'mystacornis crossleyi',
|
| 506 |
+
'nandinia binotata', 'cyanomitra cyanolaema', 'oressochen jubatus',
|
| 507 |
+
'neocossyphus rufus', 'neofelis diardi', 'neofelis nebulosa',
|
| 508 |
+
'neomorphus geoffroyi', 'neomorphus rufipennis',
|
| 509 |
+
'delacourella capistrata', 'streptopelia picturata',
|
| 510 |
+
'nesolagus netscheri', 'nesomys audeberti', 'nesotragus moschatus',
|
| 511 |
+
'caprimulgus europaeus', 'niltava sumatrana', 'nisaetus nanus',
|
| 512 |
+
'nothocrax urumutum', 'numida meleagris', 'nyctidromus albicollis',
|
| 513 |
+
'odontophorus balliviani', 'odontophorus erythrops',
|
| 514 |
+
'odontophorus gujanensis', 'oenomys hypoxanthus',
|
| 515 |
+
'ortalis guttata', 'oryx beisa', 'otolemur garnettii',
|
| 516 |
+
'otus spilocephalus', 'ovis aries', 'oxylabes madagascariensis',
|
| 517 |
+
'pan troglodytes', 'panthera tigris', 'papio anubis',
|
| 518 |
+
'papio cynocephalus', 'paraxerus boehmi', 'paraxerus cepapi',
|
| 519 |
+
'paraxerus lucifer', 'paraxerus ochraceus',
|
| 520 |
+
'paraxerus vexillarius', 'penelope purpurascens',
|
| 521 |
+
'penelope superciliaris', 'pernis ptilorhynchus',
|
| 522 |
+
'petrodromus tetradactylus', 'philander opossum',
|
| 523 |
+
'philantomba monticola', 'pilherodius pileatus',
|
| 524 |
+
'xanthomixis apperti', 'pipile cumanensis', 'pipile pipile',
|
| 525 |
+
'hydrornis guajanus', 'hydrornis schneideri', 'ploceus alienus',
|
| 526 |
+
'ploceus baglafecht', 'poecilogale albinucha',
|
| 527 |
+
'pogonocichla stellata', 'polyplectron chalcurum',
|
| 528 |
+
'erythrogenys mcclellandi', 'potos flavus', 'praomys tullbergi',
|
| 529 |
+
'presbytis femoralis', 'presbytis thomasi', 'prionodon linsang',
|
| 530 |
+
'procavia capensis', 'piliocolobus gordonorum',
|
| 531 |
+
'procyon cancrivorus', 'propithecus candidus',
|
| 532 |
+
'protoxerus stangeri', 'psophia crepitans', 'psophia leucoptera',
|
| 533 |
+
'pternistis hildebrandti', 'pternistis leucoscepus',
|
| 534 |
+
'pteroglossus beauharnaisii', 'ramphastos tucanus',
|
| 535 |
+
'rattus tiomanicus', 'rhea americana', 'rhizomys sumatrensis',
|
| 536 |
+
'rhynchocyon cirnei', 'rhynchocyon petersi',
|
| 537 |
+
'rhynchocyon udzungwensis', 'rollulus rouloul',
|
| 538 |
+
'rupornis magnirostris', 'ruwenzorornis johnstoni',
|
| 539 |
+
'saimiri boliviensis', 'salanoia concolor', 'saxicola tectes',
|
| 540 |
+
'sciurus deppei', 'sciurus granatensis', 'sciurus ignitus',
|
| 541 |
+
'sciurus spadiceus', 'setifer setosus', 'sheppardia lowei',
|
| 542 |
+
'spilogale putorius', 'spizaetus ornatus',
|
| 543 |
+
'stephanoaetus coronatus', 'stigmochelys pardalis',
|
| 544 |
+
'streptopelia capicola', 'streptopelia lugens',
|
| 545 |
+
'streptopelia senegalensis', 'amazona oratrix', 'suncus murinus',
|
| 546 |
+
'sundasciurus hippurus', 'sus barbatus', 'sylvilagus brasiliensis',
|
| 547 |
+
'tamandua mexicana', 'tapirus bairdii', 'tapirus indicus',
|
| 548 |
+
'tauraco livingstonii', 'tenrec ecaudatus', 'terpsiphone mutata',
|
| 549 |
+
'thamnomys venustus', 'thryonomys gregorianus',
|
| 550 |
+
'thryonomys swinderianus', 'tigrisoma lineatum',
|
| 551 |
+
'tigrisoma mexicanum', 'tinamus guttatus', 'tinamus tao',
|
| 552 |
+
'tockus deckeni', 'tockus flavirostris', 'tolypeutes matacus',
|
| 553 |
+
'tragelaphus imberbis', 'tragulus javanicus', 'tragulus kanchil',
|
| 554 |
+
'tragulus napu', 'tremarctos ornatus', 'trichys fasciculata',
|
| 555 |
+
'tupaia glis', 'tupinambis teguixin', 'turdus ignobilis',
|
| 556 |
+
'turdus olivaceus', 'turdus tephronotus', 'turtur chalcospilos',
|
| 557 |
+
'turtur tympanistria', 'tyto alba', 'vanellus coronatus',
|
| 558 |
+
'varanus salvator', 'vicugna pacos', 'viverricula indica',
|
| 559 |
+
'xenoperdix udzungwensis', 'euxerus erythropus', 'xerus rutilus',
|
| 560 |
+
'zonotrichia capensis', 'erinaceus europaeus', 'rattus norvegicus'
|
| 561 |
+
]),
|
| 562 |
+
"subspecies": datasets.ClassLabel(num_classes=8, names=[
|
| 563 |
+
'sciurus niger cinereus', 'alces alces americanus',
|
| 564 |
+
'sapajus apella margaritae', 'damaliscus pygargus phillipsi',
|
| 565 |
+
'alcelaphus buselaphus caama', 'damaliscus lunatus jimela',
|
| 566 |
+
'equus quagga burchellii', 'zoothera dauma dauma'
|
| 567 |
+
]),
|
| 568 |
+
"variety": datasets.ClassLabel(num_classes=1, names=[
|
| 569 |
+
'gallus gallus domesticus'
|
| 570 |
+
]),
|
| 571 |
+
}
|
| 572 |
+
|
| 573 |
+
|
| 574 |
class LILAConfig(datasets.BuilderConfig):
|
| 575 |
"""Builder Config for LILA"""
|
| 576 |
|
|
|
|
| 607 |
"id": datasets.Value("string"), "file_name": datasets.Value("string"),
|
| 608 |
"width": datasets.Value("int32"), "height": datasets.Value("int32"),
|
| 609 |
"seq_num_frames": datasets.Value("int32"),
|
| 610 |
+
"date_captured": datasets.Value("string"), # TODO: Preprocess so that it can be formatted as date...
|
| 611 |
"seq_id": datasets.Value("string"),
|
| 612 |
"location": datasets.Value("string"),
|
| 613 |
"rights_holder": datasets.Value("string"),
|
|
|
|
| 615 |
"annotations": datasets.Sequence({
|
| 616 |
"id": datasets.Value("string"),
|
| 617 |
"category_id": datasets.Value("int32"),
|
| 618 |
+
"taxonomy": _TAXONOMY,
|
| 619 |
}),
|
| 620 |
"bboxes": datasets.Sequence({
|
| 621 |
"id": datasets.Value("string"),
|
|
|
|
| 632 |
"id": datasets.Value("string"),
|
| 633 |
"category_id": datasets.Value("int32"),
|
| 634 |
"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
|
| 635 |
+
"taxonomy": _TAXONOMY,
|
| 636 |
}),
|
| 637 |
"image": datasets.Image(decode=False),
|
| 638 |
})
|
|
|
|
| 647 |
"category_id": datasets.Value("int32"),
|
| 648 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 649 |
"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
|
| 650 |
+
"taxonomy": _TAXONOMY,
|
| 651 |
}),
|
| 652 |
"image": datasets.Image(decode=False),
|
| 653 |
})
|
|
|
|
| 659 |
"annotations": datasets.Sequence({
|
| 660 |
"id": datasets.Value("string"),
|
| 661 |
"category_id": datasets.Value("int32"),
|
| 662 |
+
"taxonomy": _TAXONOMY,
|
| 663 |
}),
|
| 664 |
"bboxes": datasets.Sequence({
|
| 665 |
"id": datasets.Value("string"),
|
|
|
|
| 677 |
"seq_id": datasets.Value("string"), "country_code": datasets.Value("string"),
|
| 678 |
"seq_num_frames": datasets.Value("int32"),
|
| 679 |
"status": datasets.Value("string"),
|
| 680 |
+
"datetime": datasets.Value("string"),
|
| 681 |
"corrupt": datasets.Value("bool"),
|
| 682 |
"annotations": datasets.Sequence({
|
| 683 |
"id": datasets.Value("string"),
|
|
|
|
| 685 |
"count": datasets.Value("int32"),
|
| 686 |
"sex": datasets.Value("string"),
|
| 687 |
"age": datasets.Value("string"),
|
| 688 |
+
"taxonomy": _TAXONOMY,
|
| 689 |
}),
|
| 690 |
"bboxes": datasets.Sequence({
|
| 691 |
"id": datasets.Value("string"),
|
|
|
|
| 700 |
"width": datasets.Value("int32"), "height": datasets.Value("int32"),
|
| 701 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 702 |
"site": datasets.Value("string"), "camera": datasets.Value("string"),
|
| 703 |
+
"datetime": datasets.Value("string"),
|
| 704 |
"annotations": datasets.Sequence({
|
| 705 |
"id": datasets.Value("string"),
|
| 706 |
"category_id": datasets.Value("int32"),
|
| 707 |
+
"taxonomy": _TAXONOMY,
|
| 708 |
}),
|
| 709 |
"image": datasets.Image(decode=False),
|
| 710 |
})
|
|
|
|
| 716 |
"id": datasets.Value("string"),
|
| 717 |
"category_id": datasets.Value("int32"),
|
| 718 |
"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
|
| 719 |
+
"taxonomy": _TAXONOMY,
|
| 720 |
}),
|
| 721 |
"image": datasets.Image(decode=False),
|
| 722 |
})
|
|
|
|
| 734 |
"category_id": datasets.Value("int32"),
|
| 735 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 736 |
"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
|
| 737 |
+
"taxonomy": _TAXONOMY,
|
| 738 |
}),
|
| 739 |
"image": datasets.Image(decode=False),
|
| 740 |
})
|
|
|
|
| 744 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 745 |
"seq_num_frames": datasets.Value("int32"),
|
| 746 |
"original_relative_path": datasets.Value("string"),
|
| 747 |
+
"datetime": datasets.Value("string"),
|
| 748 |
"location": datasets.Value("string"),
|
| 749 |
"annotations": datasets.Sequence({
|
| 750 |
"id": datasets.Value("string"),
|
| 751 |
"category_id": datasets.Value("int32"),
|
| 752 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 753 |
+
"taxonomy": _TAXONOMY,
|
| 754 |
}),
|
| 755 |
"image": datasets.Image(decode=False),
|
| 756 |
})
|
|
|
|
| 760 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 761 |
"width": datasets.Value("int32"), "height": datasets.Value("int32"),
|
| 762 |
"seq_num_frames": datasets.Value("int32"),
|
| 763 |
+
"datetime": datasets.Value("string"),
|
| 764 |
"corrupt": datasets.Value("bool"),
|
| 765 |
"location": datasets.Value("string"),
|
| 766 |
"annotations": datasets.Sequence({
|
|
|
|
| 769 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 770 |
"seq_id": datasets.Value("string"),
|
| 771 |
"season": datasets.Value("string"),
|
| 772 |
+
"datetime": datasets.Value("string"),
|
| 773 |
"subject_id": datasets.Value("string"),
|
| 774 |
"count": datasets.Value("string"),
|
| 775 |
"standing": datasets.Value("float32"),
|
|
|
|
| 778 |
"interacting": datasets.Value("float32"),
|
| 779 |
"young_present": datasets.Value("float32"),
|
| 780 |
"location": datasets.Value("string"),
|
| 781 |
+
"taxonomy": _TAXONOMY,
|
| 782 |
}),
|
| 783 |
"bboxes": datasets.Sequence({
|
| 784 |
"id": datasets.Value("string"),
|
|
|
|
| 796 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 797 |
"width": datasets.Value("int32"), "height": datasets.Value("int32"),
|
| 798 |
"seq_num_frames": datasets.Value("int32"),
|
| 799 |
+
"datetime": datasets.Value("string"),
|
| 800 |
"corrupt": datasets.Value("bool"),
|
| 801 |
"location": datasets.Value("string"),
|
| 802 |
"annotations": datasets.Sequence({
|
|
|
|
| 805 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 806 |
"seq_id": datasets.Value("string"),
|
| 807 |
"season": datasets.Value("string"),
|
| 808 |
+
"datetime": datasets.Value("string"),
|
| 809 |
"subject_id": datasets.Value("string"),
|
| 810 |
"count": datasets.Value("string"),
|
| 811 |
"standing": datasets.Value("float32"),
|
|
|
|
| 814 |
"interacting": datasets.Value("float32"),
|
| 815 |
"young_present": datasets.Value("float32"),
|
| 816 |
"location": datasets.Value("string"),
|
| 817 |
+
"taxonomy": _TAXONOMY,
|
| 818 |
+
}),
|
| 819 |
+
"image": datasets.Image(decode=False),
|
| 820 |
+
})
|
| 821 |
+
elif self.config.name == 'SWG Camera Traps':
|
| 822 |
+
return datasets.Features({
|
| 823 |
+
"id": datasets.Value("string"), "file_name": datasets.Value("string"),
|
| 824 |
+
"width": datasets.Value("int32"), "height": datasets.Value("int32"),
|
| 825 |
+
"location": datasets.Value("string"),
|
| 826 |
+
"frame_num": datasets.Value("int32"),
|
| 827 |
+
"seq_id": datasets.Value("string"),
|
| 828 |
+
"seq_num_frames": datasets.Value("int32"),
|
| 829 |
+
"datetime": datasets.Value("string"),
|
| 830 |
+
"corrupt": datasets.Value("bool"),
|
| 831 |
+
"annotations": datasets.Sequence({
|
| 832 |
+
"id": datasets.Value("string"),
|
| 833 |
+
"sequence_level_annotation": datasets.Value("bool"),
|
| 834 |
+
"category_id": datasets.Value("int32"),
|
| 835 |
+
"taxonomy": _TAXONOMY,
|
| 836 |
+
}),
|
| 837 |
+
"bboxes": datasets.Sequence({
|
| 838 |
+
"id": datasets.Value("string"),
|
| 839 |
+
"category_id": datasets.Value("int32"),
|
| 840 |
+
"sequence_level_annotation": datasets.Value("bool"),
|
| 841 |
+
"bbox": datasets.Sequence(datasets.Value("float32"), length=4),
|
| 842 |
}),
|
| 843 |
"image": datasets.Image(decode=False),
|
| 844 |
})
|
|
|
|
| 846 |
return datasets.Features({
|
| 847 |
"id": datasets.Value("string"), "file_name": datasets.Value("string"),
|
| 848 |
"frame_num": datasets.Value("int32"), "seq_id": datasets.Value("string"),
|
| 849 |
+
"seq_num_frames": datasets.Value("int32"), "datetime": datasets.Value("string"),
|
| 850 |
"location": datasets.Value("string"),
|
| 851 |
"annotations": datasets.Sequence({
|
| 852 |
"id": datasets.Value("string"),
|
| 853 |
"sequence_level_annotation": datasets.Value("bool"),
|
| 854 |
"category_id": datasets.Value("int32"),
|
| 855 |
+
"taxonomy": _TAXONOMY,
|
| 856 |
}),
|
| 857 |
"image": datasets.Image(decode=False),
|
| 858 |
})
|
|
|
|
| 878 |
|
| 879 |
def _split_generators(self, dl_manager):
|
| 880 |
archive_path = dl_manager.download_and_extract(self.config.metadata_url)
|
| 881 |
+
if archive_path.endswith(".zip") or os.path.isdir(archive_path):
|
| 882 |
archive_path = os.path.join(archive_path, os.listdir(archive_path)[0])
|
| 883 |
|
| 884 |
return [
|