README.md

---
library_name: tensorflow-lite
license: other
tags:
- android
- on-device-training
- fire-detection
---

# FireViewer · LiteRT conversion archive


## Quick card

| Field | Reference |
| --- | --- |
| Use | Inspect an archived LiteRT conversion and its precise output contract. |
| Expected input | Matching image/ROI tensors, labels, coordinate transforms and runtime contract. |
| Example | Invoke the documented inference signature; adapt reviewed targets only for historical graphs exposing genuine training signatures. |
| Limits | Export and SDK receipts concern these converted graphs. Native research-model evaluation remains separate. |
| Contract | [Conversion guide](docs/CHOOSING_VARIANTS.md) · [Per-variant cards](#catalogue-and-recorded-qualification) |

Ten retained conversion packages: six historical variants, including five trainable heads/output adapters, and four FP32 inference-only exports. The original artifacts, technical contracts and SDK receipts are preserved.

[Conversion guide](docs/CHOOSING_VARIANTS.md) · [Usage guide](docs/USAGE.en.md) · [Conversion evidence](docs/BENCHMARKS.en.md) · [Update log](CHANGELOG.md)

## Retained FP32 exports

| Package | Input | Conversion contract |
| --- | --- | --- |
| [fireviewer_dinov2_small_fire_associated_smoke_v25_fp32](models/fireviewer_dinov2_small_fire_associated_smoke_v25_fp32/README.md) | Exact tensor signature in contract | [runtime_contract.json](models/fireviewer_dinov2_small_fire_associated_smoke_v25_fp32/runtime_contract.json) |
| [fireviewer_dinov2_small_visible_flame_monopoint_v25_fp32](models/fireviewer_dinov2_small_visible_flame_monopoint_v25_fp32/README.md) | Exact tensor signature in contract | [runtime_contract.json](models/fireviewer_dinov2_small_visible_flame_monopoint_v25_fp32/runtime_contract.json) |
| [fireviewer_rfdetr_medium_probable_fire_v25_fp32](models/fireviewer_rfdetr_medium_probable_fire_v25_fp32/README.md) | Exact tensor signature in contract | [runtime_contract.json](models/fireviewer_rfdetr_medium_probable_fire_v25_fp32/runtime_contract.json) |
| [fireviewer_rfdetr_medium_visible_flame_v25_fp32](models/fireviewer_rfdetr_medium_visible_flame_v25_fp32/README.md) | Exact tensor signature in contract | [runtime_contract.json](models/fireviewer_rfdetr_medium_visible_flame_v25_fp32/runtime_contract.json) |

These four exports expose inference only. Their tensor-parity and frozen operating-point checks are conversion evidence; the native cascade diagnostic is documented in its own research presentation.

## Catalogue and recorded qualification

| Variant | Synthetic host learning | Standalone Android SDK | Vision Dataset Studio |
| --- | --- | --- | --- |
| [D-FINE M strict v1, learning](models/fireviewer_dfine_m_strict_v1_learning/README.md) | PASS | Not qualified | Not qualified |
| [RT-DETRv2 R50, learning](models/fireviewer_rtdetr_v2_r50_learning/README.md) | PASS | Not qualified | Not qualified |
| [YOLO11 M strict v1, inference](models/fireviewer_yolo11m_strict_v1/README.md) | N/A | Not qualified | Not qualified |
| [YOLO11 M strict v1, learning](models/fireviewer_yolo11m_strict_v1_learning/README.md) | PASS | PASS on emulator | Not qualified |
| [RF-DETR Medium 1.10, learning](models/fireviewer_rfdetr_medium_v110_learning/README.md) | PASS | Not qualified | Not qualified |
| [DINOv3 pointing pilot v1, learning](models/fireviewer_dinov3_pointing_pilot_v1_learning/README.md) | PASS | Not qualified | Not qualified |

![Historical conversion and SDK qualification matrix](docs/figures/qualification-matrix.png)

The retained [delivery receipt](reports/fireviewer-completion.json) covers five
learning conversions. The YOLO inference-only graph is a sixth delivered variant.
No SegFormer graph is delivered because the optional source was unavailable.
Detection adapters cannot create proposals absent from the frozen detector.

**The six historical variants remain unqualified inside Vision Dataset Studio.** The YOLO
learning SDK pass does not qualify other models, application integration or a
physical ARM phone. For those six historical variants, task accuracy, generalization and forgetting are unmeasured.

## Download and integrate

Choose a variant and read its README, runtime contract, artifact manifest and
source notices. Retrieve all matching files at the same immutable revision:

```python
from huggingface_hub import hf_hub_download

contract = hf_hub_download(
    repo_id="fireviewer/litert-models",
    revision="bdcd483d5c5aadeff1b531a35b536f3530906e18",
    filename="models/fireviewer_yolo11m_strict_v1_learning/runtime_contract.json",
)
```

Apply the exact normalization, tensor layout, labels and coordinate transform.
Check inference before learning, train only with reviewed targets, keep the
original weights, and store checkpoints separately. Evaluate adapted candidates
before activation. See the [complete usage guide](docs/USAGE.en.md).

## SDK and runtime contract

The Kotlin SDK exposes `infer`, `train`, `save` and `restore`. Checkpoints preserve
parameters, SGD momentum and step counters; receipts check model/label identity
and file integrity. The integrating application selects the active checkpoint.

YOLO supports image dimensions that are multiples of 32. Other graphs resize to
their internal grid. The historical SDK uses TensorFlow Lite and Select TF Ops
**2.16.1**. Vision Dataset Studio's separate 16 KB Flex fix does not retroactively
qualify this SDK. [Conversion sources](conversion/README.md).

## Rights and responsible use

Source weights, datasets and software retain their own licences and restrictions.
Read each variant's notices; download access alone grants no commercial-use or
redistribution permission. In particular, YOLO upstream obligations and the
DINOv3 pilot's retained release policy remain applicable.

Synthetic checks establish parameter updates and persistence, not field accuracy
or reliable alerts. These models must not be used alone to confirm a fire,
trigger an emergency alert, order an evacuation or direct emergency response.

## Documentation and revision

Historical catalogue documentation updated in English on **5 October 2026**, from the public repository at
[`bdcd483d5c5aadeff1b531a35b536f3530906e18`](https://huggingface.co/fireviewer/litert-models/tree/bdcd483d5c5aadeff1b531a35b536f3530906e18) and its retained reports.
This update checks documentation, repository metadata and small evidence files;
it does not rerun training, inference, dataset payload verification or device qualification.
Historical receipts keep their original dates, revisions and scope. Earlier README
hashes in artifact manifests refer to those earlier releases.

The association FIRE-VIEWER provides administrative and financial stewardship for
resources under its control. Technical governance is maintainer-led. Upstream,
source-specific and pre-association rights remain separate; repository placement
does not transfer ownership or grant additional rights.

[Project documentation](https://github.com/fireviewer/Fireviewer_doc/blob/main/docs/public/HUGGINGFACE.md)
· [Institutional website](https://fire-viewer.fr). Contact: **contact@fire-viewer.fr**.

**Likes are always welcome! ❤️** If these resources help you, a little heart makes our day and helps others discover the work. Thank you!