Datasets:

License:
admin commited on
Commit
d396904
·
1 Parent(s): 586d4ca
Files changed (2) hide show
  1. README.md +1 -1
  2. insecta.py +13 -23
README.md CHANGED
@@ -20,7 +20,7 @@ from datasets import load_dataset
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  ds = load_dataset(
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  "Genius-Society/insecta",
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- split="test",
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  cache_dir="./__pycache__",
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  trust_remote_code=True,
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  )
 
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  ds = load_dataset(
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  "Genius-Society/insecta",
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+ split="train",
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  cache_dir="./__pycache__",
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  trust_remote_code=True,
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  )
insecta.py CHANGED
@@ -19,9 +19,10 @@ class insecta(datasets.GeneratorBasedBuilder):
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  {
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  "image": datasets.Image(),
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  "label": datasets.Value("string"),
 
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  }
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  ),
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- supervised_keys=("image", "label"),
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  homepage=_URL,
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  license="mit",
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  version="0.0.1",
@@ -65,40 +66,29 @@ class insecta(datasets.GeneratorBasedBuilder):
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  files = self._get_files("已鉴定")
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  for file in tqdm(files, desc="Parsing classes"):
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  imgs = self._get_files(file["Path"])
 
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  for img in imgs:
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  dataset.append(
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  {
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- "image": self._dld_img(f"{_URL}/resolve/master/" + img["Path"]),
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- "label": file["Name"],
 
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  }
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  )
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  random.shuffle(dataset)
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- data_count = len(dataset)
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- p80 = int(data_count * 0.8)
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- p90 = int(data_count * 0.9)
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  return [
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  datasets.SplitGenerator(
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  name=datasets.Split.TRAIN,
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- gen_kwargs={
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- "files": dataset[:p80],
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- },
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.VALIDATION,
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- gen_kwargs={
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- "files": dataset[p80:p90],
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- },
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- gen_kwargs={
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- "files": dataset[p90:],
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- },
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- ),
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  ]
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  def _generate_examples(self, files):
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  for i, path in enumerate(files):
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- yield i, path
 
 
 
 
 
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  {
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  "image": datasets.Image(),
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  "label": datasets.Value("string"),
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+ "latin": datasets.Value("string"),
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  }
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  ),
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+ supervised_keys=("image", "latin"),
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  homepage=_URL,
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  license="mit",
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  version="0.0.1",
 
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  files = self._get_files("已鉴定")
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  for file in tqdm(files, desc="Parsing classes"):
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  imgs = self._get_files(file["Path"])
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+ label, latin = str(file["Name"]).split(" ", 1)
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  for img in imgs:
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  dataset.append(
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  {
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+ "image": f"{_URL}/resolve/master/" + img["Path"],
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+ "label": label.strip(),
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+ "latin": latin.strip(),
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  }
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  )
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  random.shuffle(dataset)
 
 
 
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  return [
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  datasets.SplitGenerator(
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  name=datasets.Split.TRAIN,
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+ gen_kwargs={"files": dataset},
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+ )
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ]
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  def _generate_examples(self, files):
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  for i, path in enumerate(files):
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+ yield i, {
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+ "image": self._dld_img(path["image"]),
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+ "label": path["label"],
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+ "latin": path["latin"],
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+ }