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--- |
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dataset_info: |
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features: |
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- name: scene |
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dtype: string |
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- name: image |
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dtype: image |
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- name: depth_map |
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dtype: image |
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- name: direction |
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dtype: string |
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- name: temprature |
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dtype: int32 |
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- name: caption |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 20575644792.0 |
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num_examples: 12000 |
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download_size: 20108431280 |
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dataset_size: 20575644792.0 |
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--- |
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# VIDIT Dataset |
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This is a version of the [VIDIT dataset](https://github.com/majedelhelou/VIDIT) equipped for training ControlNet using depth maps conditioning. |
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VIDIT includes 390 different Unreal Engine scenes, each captured with 40 illumination settings, resulting in 15,600 images. The illumination settings are all the combinations of 5 color temperatures (2500K, 3500K, 4500K, 5500K and 6500K) and 8 light directions (N, NE, E, SE, S, SW, W, NW). Original image resolution is 1024x1024. |
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We include in this version only the training split containing only 300 scenes. |
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Captions were generated using the [BLIP-2, Flan T5-xxl](https://huggingface.co/Salesforce/blip2-flan-t5-xxl) model. |
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Depth maps were generated using the [GLPN fine-tuned on NYUv2 ](https://huggingface.co/vinvino02/glpn-nyu) model. |
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## Examples with varying direction |
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![varying direction](B_directions.gif) |
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## Examples with varying color temperature |
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![varying color temperature](B_illuminants.gif) |
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## Disclaimer |
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I do not own any of this data. |
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