ultralytics 8.3.70 add data argument to Sony IMX500 export (#18852)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Francesco Mattioli <Francesco.mttl@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Lakshantha Dissanayake 2025-01-30 03:28:19 -08:00 committed by GitHub
parent ec622230fb
commit f38fa61ffc
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
6 changed files with 47 additions and 36 deletions

View file

@ -59,14 +59,19 @@ Export a YOLOv8n model to OpenVINO format and run inference with the exported mo
## Arguments
| Key | Value | Description |
| --------- | ------------ | --------------------------------------------------------------------------- |
| `format` | `'openvino'` | format to export to |
| `imgsz` | `640` | image size as scalar or (h, w) list, i.e. (640, 480) |
| `half` | `False` | FP16 quantization |
| `int8` | `False` | INT8 quantization |
| `batch` | `1` | [batch size](https://www.ultralytics.com/glossary/batch-size) for inference |
| `dynamic` | `False` | allows dynamic input sizes |
| Key | Value | Description |
| --------- | ------------ | ------------------------------------------------------------------------------------------- |
| `format` | `'openvino'` | format to export to |
| `imgsz` | `640` | image size as scalar or (h, w) list, i.e. (640, 480) |
| `half` | `False` | FP16 quantization |
| `int8` | `False` | INT8 quantization |
| `batch` | `1` | [batch size](https://www.ultralytics.com/glossary/batch-size) for inference |
| `dynamic` | `False` | allows dynamic input sizes |
| `data` | `coco8.yaml` | Path to the dataset configuration file (default: `coco8.yaml`), essential for quantization. |
!!! note
When using `data` argument for quantization, please check [Dataset Guide](https://docs.ultralytics.com/datasets/detect) to learn more about the dataset format.
## Benefits of OpenVINO