HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

ultralytics 8.1.6 revert 8.0.206 box ops box scaling (#7823)

Browse source 
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Abirami Vina <abirami.vina@gmail.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
This commit is contained in:
Glenn Jocher 2024-01-25 21:29:49 +01:00 • committed by GitHub
parent 1a04cd38e7
commit ef141af4b8
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
17 changed files with 416 additions and 36 deletions
Download patch file Download diff file Expand all files Collapse all files

32
docs/en/models/fast-sam.md
View file

@ -156,28 +156,28 @@ FastSAM is also available directly from the [https://github.com/CASIA-IVA-Lab/Fa
2. Use FastSAM for inference. Example commands:
- Segment everything in an image:
- Segment everything in an image:
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg
```
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg
```
- Segment specific objects using text prompt:
- Segment specific objects using text prompt:
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --text_prompt "the yellow dog"
```
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --text_prompt "the yellow dog"
```
- Segment objects within a bounding box (provide box coordinates in xywh format):
- Segment objects within a bounding box (provide box coordinates in xywh format):
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --box_prompt "[570,200,230,400]"
```
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --box_prompt "[570,200,230,400]"
```
- Segment objects near specific points:
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --point_prompt "[[520,360],[620,300]]" --point_label "[1,0]"
```
- Segment objects near specific points:
```shell
python Inference.py --model_path ./weights/FastSAM.pt --img_path ./images/dogs.jpg --point_prompt "[[520,360],[620,300]]" --point_label "[1,0]"
```
Additionally, you can try FastSAM through a [Colab demo](https://colab.research.google.com/drive/1oX14f6IneGGw612WgVlAiy91UHwFAvr9?usp=sharing) or on the [HuggingFace web demo](https://huggingface.co/spaces/An-619/FastSAM) for a visual experience.