Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,32 @@
|
|
1 |
-
---
|
2 |
-
license: agpl-3.0
|
3 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: agpl-3.0
|
3 |
+
---
|
4 |
+
|
5 |
+

|
6 |
+
|
7 |
+
## YOLOv8s: Target Detection
|
8 |
+
|
9 |
+
YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
|
10 |
+
|
11 |
+
### Source model
|
12 |
+
|
13 |
+
- Input shape: 640x640
|
14 |
+
- Number of parameters: 10.65M
|
15 |
+
- Model size: 42.7MB
|
16 |
+
- Output shape: 1x84x8400
|
17 |
+
|
18 |
+
Source model repository: [yolov8](https://github.com/ultralytics/ultralytics)
|
19 |
+
|
20 |
+
## Performance Reference
|
21 |
+
|
22 |
+
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
|
23 |
+
|
24 |
+
## Inference & Model Conversion
|
25 |
+
|
26 |
+
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
|
27 |
+
|
28 |
+
## License
|
29 |
+
|
30 |
+
- Source Model: [AGPL-3.0](https://github.com/ultralytics/ultralytics/blob/main/LICENSE)
|
31 |
+
|
32 |
+
- Deployable Model: [AGPL-3.0](https://github.com/ultralytics/ultralytics/blob/main/LICENSE)
|