xiaohk commited on
Commit
965466d
1 Parent(s): 91021eb

Change pyarrow to pandas for dataset preview

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Files changed (1) hide show
  1. diffusiondb.py +11 -15
diffusiondb.py CHANGED
@@ -11,8 +11,6 @@ from os.path import join, basename
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  from huggingface_hub import hf_hub_url
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  import datasets
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- import pyarrow as pa
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- import pyarrow.parquet as pq
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  # Find for instance the citation on arxiv or on the dataset repo/website
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  _CITATION = """\
@@ -359,11 +357,12 @@ class DiffusionDB(datasets.GeneratorBasedBuilder):
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  cur_id = int(re.sub(r"part-(\d+)\.json", r"\1", basename(path)))
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  part_ids.append(cur_id)
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- metadata_table = pq.read_table(
 
 
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  metadata_path,
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  filters=[("part_id", "in", part_ids)],
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  )
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- print(metadata_table.shape)
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  # Iterate through all extracted zip folders for images
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  for k in range(num_data_dirs):
@@ -376,11 +375,8 @@ class DiffusionDB(datasets.GeneratorBasedBuilder):
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  img_params = json_data[img_name]
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  img_path = join(cur_data_dir, img_name)
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- # Query the meta data
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- row_mask = pa.compute.equal(
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- metadata_table.column("image_name"), img_name
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- )
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- query_result = metadata_table.filter(row_mask)
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  # Yields examples as (key, example) tuples
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  yield img_name, {
@@ -393,10 +389,10 @@ class DiffusionDB(datasets.GeneratorBasedBuilder):
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  "step": int(img_params["st"]),
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  "cfg": float(img_params["c"]),
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  "sampler": img_params["sa"],
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- "width": query_result["width"][0].as_py(),
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- "height": query_result["height"][0].as_py(),
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- "user_name": query_result["user_name"][0].as_py(),
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- "timestamp": query_result["timestamp"][0].as_py(),
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- "image_nsfw": query_result["image_nsfw"][0].as_py(),
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- "prompt_nsfw": query_result["prompt_nsfw"][0].as_py(),
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  }
 
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  from huggingface_hub import hf_hub_url
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  import datasets
 
 
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  # Find for instance the citation on arxiv or on the dataset repo/website
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  _CITATION = """\
 
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  cur_id = int(re.sub(r"part-(\d+)\.json", r"\1", basename(path)))
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  part_ids.append(cur_id)
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+ # We have to use pandas here to make the dataset preview work (it
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+ # uses streaming mode)
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+ metadata_table = pd.read_parquet(
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  metadata_path,
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  filters=[("part_id", "in", part_ids)],
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  )
 
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  # Iterate through all extracted zip folders for images
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  for k in range(num_data_dirs):
 
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  img_params = json_data[img_name]
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  img_path = join(cur_data_dir, img_name)
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+ # Query the metadata
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+ query_result = metadata_table.query(f'`image_name` == "{img_name}"')
 
 
 
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  # Yields examples as (key, example) tuples
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  yield img_name, {
 
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  "step": int(img_params["st"]),
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  "cfg": float(img_params["c"]),
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  "sampler": img_params["sa"],
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+ "width": query_result["width"].to_list()[0],
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+ "height": query_result["height"].to_list()[0],
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+ "user_name": query_result["user_name"].to_list()[0],
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+ "timestamp": query_result["timestamp"].to_list()[0],
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+ "image_nsfw": query_result["image_nsfw"].to_list()[0],
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+ "prompt_nsfw": query_result["prompt_nsfw"].to_list()[0],
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  }