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--- |
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datasets: lh9171338/Wireframe |
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pretty_name: Wireframe Dataset |
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license: mit |
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tags: |
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- computer-vision |
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- line-segment-detection |
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- wireframe-parsing |
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size_categories: 1K<n<10K |
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--- |
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# Wireframe Dataset |
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This is the [Wireframe dataset](https://github.com/huangkuns/wireframe) hosted on Hugging Face Hub. |
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## Summary |
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Wireframe dataset with image annotations including line segments. |
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The dataset is stored as jsonl files (`train/metadata.jsonl`, `test/metadata.jsonl`) and images. |
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Number of samples: |
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- Train: 5,000 |
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- Test: 462 |
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## Download |
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- Download with huggingface-hub |
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```shell |
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python3 -m pip install huggingface-hub |
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huggingface-cli download --repo-type dataset lh9171338/Wireframe --local-dir ./ |
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``` |
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- Download with Git |
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```shell |
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git lfs install |
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git clone https://huggingface.co/datasets/lh9171338/Wireframe |
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``` |
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## Usage |
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- Load the dataset from Hugging Face Hub |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("lh9171338/Wireframe") |
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# or load from `refs/convert/parquet` for acceleration |
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# from datasets import load_dataset, Features, Image, Sequence, Value |
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# features = Features({ |
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# "image": Image(), |
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# "image_file": Value("string"), |
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# "image_size": Sequence(Value("int32")), |
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# "lines": Sequence(Sequence(Sequence(Value("float32")))), |
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# }) |
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# ds = load_dataset("lh9171338/Wireframe", features=features, revision="refs/convert/parquet") |
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print(ds) |
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# DatasetDict({ |
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# train: Dataset({ |
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# features: ['image', 'image_file', 'image_size', 'lines'], |
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# num_rows: 5000 |
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# }) |
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# test: Dataset({ |
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# features: ['image', 'image_file', 'image_size', 'lines'], |
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# num_rows: 462 |
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# }) |
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# }) |
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print(ds["train"][0].keys()) |
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# dict_keys(['image', 'image_file', 'image_size', 'lines']) |
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``` |
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- Load the dataset from local |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("imagefolder", data_dir=".") |
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print(ds) |
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# DatasetDict({ |
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# train: Dataset({ |
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# features: ['image', 'image_file', 'image_size', 'lines'], |
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# num_rows: 5000 |
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# }) |
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# test: Dataset({ |
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# features: ['image', 'image_file', 'image_size', 'lines'], |
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# num_rows: 462 |
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# }) |
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# }) |
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print(ds["train"][0].keys()) |
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# dict_keys(['image', 'image_file', 'image_size', 'lines']) |
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``` |
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- Load the dataset with jsonl files |
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```python |
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import jsonlines |
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with jsonlines.open("train/metadata.jsonl") as reader: |
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infos = list(reader) |
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print(infos[0].keys()) |
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# dict_keys(['file_name', 'image_file', 'image_size', 'lines']) |
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``` |
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## Viewer |
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[Open in Space](https://huggingface.co/spaces/lh9171338/LineViewer) |
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