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schirrmacher
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humans

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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    DataFilesNotFoundError
Message:      No (supported) data files found in schirrmacher/humans
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 72, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1904, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1270, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 597, in infer_module_for_data_files
                  raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
              datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in schirrmacher/humans

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Human Segmentation Dataset

>>> Download Here <<<

This dataset was created for developing the best fully open-source background remover of images with humans. It was crafted with LayerDiffuse, a Stable Diffusion extension for generating transparent images. After creating segmented humans, IC-Light was used for embedding them into realistic scenarios.

The dataset covers a diverse set of segmented humans: various skin tones, clothes, hair styles etc. Since Stable Diffusion is not perfect, the dataset contains images with flaws. Still the dataset is good enough for training background remover models. I created more than 7.000 images with people and diverse backgrounds.

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Support

If you identify weaknesses in the data, please contact me.

I had some trouble with the Hugging Face file upload. This is why you can find the data here: Google Drive.

Research

Synthetic datasets have limitations for achieving great segmentation results. This is because artificial lighting, occlusion, scale or backgrounds create a gap between synthetic and real images. A "model trained solely on synthetic data generated with naïve domain randomization struggles to generalize on the real domain", see PEOPLESANSPEOPLE: A Synthetic Data Generator for Human-Centric Computer Vision (2022). However, hybrid training approaches seem to be promising and can even improve segmentation results.

Currently I am doing research how to close this gap. Latest research is about creating segmented humans with LayerDiffuse and then apply IC-Light for creating realistic light effects and shadows.

Changelog

08.06.2024

  • Applied IC-Light to segmented data
  • Added higher rotation angle to augmentation transformation

28.05.2024

  • Reduced blur, because it leads to blurred edges in results

26.05.2024

  • Added more diverse backgrounds (natural landscapes, streets, houses)
  • Added more close-up images
  • Added shadow augmentation
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