Datasets:
File size: 3,959 Bytes
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configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype:
image:
decode: false
- name: sha256
dtype: string
- name: width
dtype: int32
- name: height
dtype: int32
- name: split_group
dtype: string
- name: merge_role
dtype: string
- name: objects
struct:
- name: bbox
list:
list: float32
length: 4
- name: category
list: int32
splits:
- name: train
num_bytes: 26810502819
num_examples: 78455
- name: validation
num_bytes: 2096247471
num_examples: 11266
- name: test
num_bytes: 2343043141
num_examples: 13523
download_size: 31254424598
dataset_size: 31249793431
pretty_name: FireViewer · Probable fire v3 · native images
task_categories:
- object-detection
tags: [fireviewer, fire, smoke, probable-fire, native-images]
---
# Probable fire v3
A **103,244-image native corpus** for proposing visible fire-or-smoke regions under a single `probable_fire` class. It is separate from [Fire & Smoke v3](https://huggingface.co/datasets/fireviewer/fireviewer_fire_smoke_flame_v3_native) and does not automatically receive that corpus’s later additions.
| Split | Images |
|---|---:|
| `train` | 78,455 |
| `validation` | 11,266 |
| `test` | 13,523 |
## Choose the right task
| Need | Dataset | Classes |
|---|---|---|
| Propose regions containing visible fire or smoke | This repository | `0=probable_fire` |
| Distinguish and locate flame and smoke | Fire & Smoke v3 | `0=flame`, `1=smoke` |
The two corpora have different populations and revisions. Do not transfer their category IDs or annotations without an explicit conversion.
## Schema and geometry
Native images are embedded in `data/*.parquet`. `sha256` identifies source bytes; `width` and `height` give native dimensions. `split_group` retains grouping and `merge_role` records the merge role.
`objects.bbox` stores `[x, y, width, height]` in native pixels. `objects.category` uses **0=probable_fire**; the two lists align by index. The common class does not distinguish flame from smoke or certify an actual incident. It does not use the older v2.5 COCO category IDs.
## Streaming example
Install `datasets` and `pillow`, then load a pinned revision:
```python
import io
from datasets import load_dataset, Image as HFImage
from PIL import Image
ds = load_dataset(
"fireviewer/fireviewer_probable_fire_v3_native",
revision="637ddffba5442991ec4110283f1b3e49478f1a62",
split="validation",
streaming=True,
).cast_column("image", HFImage(decode=False))
sample = next(iter(ds))
image = Image.open(io.BytesIO(sample["image"]["bytes"]))
print(image.size, sample["objects"])
```
Preserve native pixel orientation, groups and splits. Transform boxes whenever images are cropped, rotated or resized.
## Evidence and rights
Counts come from the published metadata. The documentation review inspected the Parquet schema and an annotation sample; it is not exhaustive human review or proof of event-level independence.
This repository does not contain a blanket image licence or a detailed standalone provenance dossier. Public access does not establish redistribution rights. Check original sources and their conditions for the intended use. Detections remain visual estimates.
[FireViewer](https://huggingface.co/fireviewer) · [Resource catalogue](https://huggingface.co/spaces/fireviewer/README/blob/main/docs/RESOURCE_INDEX.md) · Presentation updated **14 November 2026**.
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