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  1. README.md +6 -6
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@@ -38,7 +38,7 @@ The dataset is released as anonymous review material for the accompanying paper,
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  The release contains 1,000 paired captures across anonymized real-world locations and scenes.
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  - `main`: full-resolution data for benchmark use.
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- - `preview`: flat, side-by-side PNG previews for quick inspection.
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  The location and scene names are anonymized. Identifiers such as `location_3`, `scene_4`, and `view_1` are stable dataset IDs and do not encode real place names.
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@@ -67,16 +67,16 @@ The TIFF files retain the camera-captured EXIF metadata. This includes exposure
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  +-- preview/
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  +-- metadata.jsonl
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  +-- images/
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- +-- location_<i>_scene_<j>_view_<k>_image_<n>_on_off.png
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  ```
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  In `main`, each metadata row points to one HDR on/off pair and the corresponding label masks. The real images are stored as TIFFs. Label masks cover regions relevant for detailed lighting analysis, including light bulbs, windows, mirror surfaces, transparent surfaces, metallic surfaces, cast shadows, specular highlights, and ambient light effects.
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- In `preview`, each PNG concatenates the tonemapped off/on pair horizontally for fast visual browsing. The left half is the light-off image; the right half is the light-on image.
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  ## Downloading Only The Preview
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- The preview subset is useful for checking the contents without downloading the full HDR release.
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  Using the Hugging Face CLI:
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@@ -114,10 +114,10 @@ To access the full benchmark data, download `main/**` as well.
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  `preview/metadata.jsonl` contains one row per preview image:
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- - `image_file_name`: path to the fused preview PNG.
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  - `location`, `scene`, `view`: anonymized hierarchical identifiers.
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  - `image_index`: pair index within the view.
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  ## Intended Use
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- 3DLP is designed for evaluating lighting edits against measured real-world ground truth. A typical use case is to give an image editing model the light-off image and ask it to turn the visible light probe on, or give it the light-on image and ask it to turn the probe off. The generated result can then be compared with the corresponding captured target image.
 
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  The release contains 1,000 paired captures across anonymized real-world locations and scenes.
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  - `main`: full-resolution data for benchmark use.
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+ - `preview`: flat, side-by-side JPEG previews for quick visual inspection.
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  The location and scene names are anonymized. Identifiers such as `location_3`, `scene_4`, and `view_1` are stable dataset IDs and do not encode real place names.
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  +-- preview/
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  +-- metadata.jsonl
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  +-- images/
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+ +-- location_<i>_scene_<j>_view_<k>_image_<n>_on_off.jpg
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  ```
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  In `main`, each metadata row points to one HDR on/off pair and the corresponding label masks. The real images are stored as TIFFs. Label masks cover regions relevant for detailed lighting analysis, including light bulbs, windows, mirror surfaces, transparent surfaces, metallic surfaces, cast shadows, specular highlights, and ambient light effects.
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+ In `preview`, each JPEG concatenates the tonemapped off/on pair horizontally for fast visual browsing. The left half is the light-off image; the right half is the light-on image.
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  ## Downloading Only The Preview
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+ The preview subset is useful for checking the contents without downloading the full HDR release. These files are compressed JPEG images and are intended only for quick visual inspection of the dataset diversity. They are not meant for scientific experiments or quantitative evaluation, and they may contain JPEG compression artifacts. Use the TIFF files in `main` for benchmark experiments and analysis.
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  Using the Hugging Face CLI:
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  `preview/metadata.jsonl` contains one row per preview image:
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+ - `image_file_name`: path to the fused preview JPEG.
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  - `location`, `scene`, `view`: anonymized hierarchical identifiers.
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  - `image_index`: pair index within the view.
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  ## Intended Use
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+ 3DLP is designed for evaluating lighting edits against measured real-world ground truth. A typical use case is to give an image editing model the light-off image and ask it to turn the visible light probe on, or give it the light-on image and ask it to turn the probe off. The generated result can then be compared with the corresponding captured target image.