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Datasets:
opendiffusionai
/
pexels-woman-solo

Tasks:
Text-to-Image
Size:
1K<n<10K
Tags:
pexels
License:
Dataset card Files Community
Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 408
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
                  df = pandas_read_json(f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
                  obj = self._get_object_parser(self.data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
                  self._parse()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
              ValueError: Trailing data
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
                  for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 408

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Overview

Around 8,000 hand-selected high-resolution 4k images of "a woman", suitable for both training, and "pre-training" of AI models. Images are all real-world realism based.

Background

I have been having difficulty training my early-stage txt2img model with GOOD, HIGH-RES images of what "a woman" is. Up until now, I have just been throwing a large number of random high-res images with "woman" in the auto-captioned details.

NOW, however, I have hand-selected a bunch of high-res (4k) images, with just "a woman" in it. (Well, okay, some have a dog in it, but mostly, "a woman" is the ONLY subject. No men, no crowds, no kids, no other women...)

Additionally, I have (tried to) thrown out all images with contents that I guess will be easily misconstrued by AI training. So, no "clever" photography shots, no super-wierd lighting, etc etc.

They are mostly just very simple shots.

Downloading the images

First install the pip based "txt2dataset" tool, and grab [https://huggingface.co/datasets/opendiffusionai/pexels-woman-solo/blob/main/woman-solo.jsonl](the jsonl file)

Then run

img2dataset --url_list woman-sharp.jsonl  --input_format "jsonl" \
--url_col "url" --output_format files \
--resize_mode no \
--output_folder pexels-woman-sharp --processes_count 8 --thread_count 8

.txt captions

As a temporary measure, you can steal pregenerated captions from one of the appropriate files in https://huggingface.co/datasets/opendiffusionai/pexels-photos-janpf

However, I am working on an even better set of captions for this subset of images. Stay tuned ...

Image license link

https://www.pexels.com/license/

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