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| # FireViewer v2.5 路 five related datasets | |
| [Presentation](../README.md) 路 [Resource index](RESOURCE_INDEX.md) 路 [Variant guide](CHOOSING_VARIANTS.md) | |
| Public redistributable releases and the retained training corpus are distinct. ROI counts are not independent incidents. Coordinate systems and original human annotations must be preserved. | |
| | Dataset | Role | Published population | Coordinates / targets | | |
| | --- | --- | --- | --- | | |
| | [v2.5-box-precise-and-multi-source-suplement](https://huggingface.co/datasets/fireviewer/v2.5-box-precise-and-multi-source-suplement) | Train or inspect probable-fire proposals and the separate fire/smoke annotation view. | 64,061 images; separate fire_smoke / probable_fire configurations | COCO xywh in original-image pixels | | |
| | [v2.5-specialisation-visible-fire](https://huggingface.co/datasets/fireviewer/v2.5-specialisation-visible-fire) | Inspect or train visible-flame detection on proposed regions. | 137,102 train / 14,822 validation ROIs | Boxes in crop pixels; recorded original-image ROI | | |
| | [v2.5-smoke-from-fire-probability](https://huggingface.co/datasets/fireviewer/v2.5-smoke-from-fire-probability) | Study fire-associated smoke compatibility for ROIs without confirmed flame. | 50,183 train / 12,106 validation ROIs | Binary compatibility labels; no point/mask targets | | |
| | [v2.5-visible-flame-crop-monopoint](https://huggingface.co/datasets/fireviewer/v2.5-visible-flame-crop-monopoint) | Study one visual anchor per accepted visible-flame crop. | 30,460 train / 1,812 validation crops | One pseudo-point: local, normalized and original-image coordinates | | |
| | [v2.5-visible-flame-full-image-multipoint](https://huggingface.co/datasets/fireviewer/v2.5-visible-flame-full-image-multipoint) | Study detection and multiple per-box flame anchors on original images. | 46,576 train / 7,647 validation images | Original boxes plus optional points and point_valid | | |
| ## Preserve the parent relationship | |
| Proposal and crop releases share parent source identities and partitions. Do not randomly repartition crops from one source image across train/validation/test. Keep the recorded ROI offsets when reprojecting model output. Public subsets do not reproduce the retained larger training corpus or balanced training sampler exactly. | |
| ## Independent annotations | |
| Keep the original detection boxes even where pseudo-point generation abstains. For a full-image object with `point_valid=False`, ignore only its point loss; retain its detection target. Pseudo-points are not independent human flame-base ground truth. Smoke compatibility has no spatial point or mask target in this release. | |
| ## Loading, rights and evaluation | |
| Follow each dataset鈥檚 pinned loading example and schema rather than inferring meaning from a filename. Retain source-specific redistribution restrictions, attributions, deduplication and exclusion receipts. No raw dataset payload is reverified by this documentation update. | |
| The crop datasets expose train/validation only as documented. Selected validation, pseudo-label agreement and the external 680-image cascade diagnostic have different populations; none replaces the locked final TEST. | |