File size: 2,026 Bytes
9840cf0 61e7934 9840cf0 61e7934 9840cf0 61e7934 9840cf0 61e7934 9840cf0 61e7934 9840cf0 61e7934 9a37fa8 61e7934 9a37fa8 61e7934 415ac8a 61e7934 73996e5 61e7934 73996e5 61e7934 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | ---
license: agpl-3.0
tags:
- rknn
- rknn2
- rockchip
- rk3576
- rk3588
---
# YOLO26-RKNN2-Ultralytics
> **Looking for the Rockchip Model Zoo and custom exports?** See [YOLO26-RKNN2](https://huggingface.co/HanzoHuang/YOLO26-RKNN2).
140 FP16 and INT8 YOLO26 exports for **RK3576** and **RK3588**, produced with the Ultralytics export workflow and task-specific RKNN conversion tools. Supported tasks include classification, depth, detection, oriented bounding boxes, pose, instance segmentation, and semantic segmentation.
## Choose a model
Models are organized by toolkit version, task, variant, target chip, and precision:
```text
models/v<toolkit-version>/<task>/<variant>/<chip>/<precision>/
```
Download `model.rknn` and `metadata.yaml` from the same directory. The [manifest](manifest.json) lists the available models and checksums.
## INT8 detection
Use the `metadata.yaml` from the same model directory. INT8 detection outputs normalized box coordinates and requires `coordinates: normalized`. Import both files together in the warehouse, or keep them in the same directory for the CLI. Treating normalized coordinates as pixels can result in no boxes.
## Reproduce the conversion
The [source directory](tree/main/source) contains the original checkpoints, conversion scripts, and environment and calibration records. Conversion used [RKNN Toolkit2 2.3.2](https://github.com/airockchip/rknn-toolkit2); upstream Ultralytics source is available on [PyPI](https://pypi.org/project/ultralytics/#history).
```bash
python source/convert-model.py --help
```
For INT8 detection, pass a COCO128 dataset YAML. For other INT8 tasks, pass a COCO128 image list. Use `--calibration-limit 128` and the input size listed in the manifest.
## Source and license
The inputs are official Ultralytics checkpoints. Conversion changes the format and quantizes the INT8 graphs. The RKNN files and original weights are distributed under AGPL-3.0; see [LICENSE](LICENSE) and the [checkpoint URLs and hashes](source/weights.json).
|