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### Search before asking
- [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussi…
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```
everything_results = model(input_image, device="cuda:0", retina_masks=args.retina, imgsz=args.imgsz, conf=args.conf, iou=args.iou)
print("model loaded " , everything_results)
```
用…
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Hi, how to make the color non randomize ? My use case is trying to create consistent color so that it can be used for ebsynth (maybe)
Thanks
x4080 updated
5 months ago
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When I trained FastSAM on coco128-seg dataset, I found that the part that needed training was the YOLOV8-seg model. So FastSam is only to train a YOLOV8-seg and then adding prompting oprations to it?
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I use the training code
`from ultralytics import YOLO
if __name__ == '__main__':
model = YOLO(model="FastSAM-x.pt")
model.train(data="aaa.yaml",
epochs=200,
…
xpbag updated
1 month ago
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Hi!
Is it possible to use without cuda?
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Does anyone have advice on how to work with the results to extract points of the mask that is generated? I have searched the docs, comments, and python files but cannot find methods to extract the mas…
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Hello,
First, thank you for this amazing repo! I have a question regarding the usage of custom trained models with CoreML INT8 export.
In the documentation, you mentioned:
> Export CoreML IN…
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Thank you for extending FastSAM to incorporate category segmentation capability. We have recommended this work in the "update" section of [FastSAM's GitHub README](https://github.com/CASIA-IVA-Lab/Fas…
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Segmenting images with many distinct objects results in many objects being missed, e.g.:
![image](https://github.com/microsoft/SoM/assets/774615/182ca8d3-8449-4edb-a3f8-99e871b05a77)
(Notice not…