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YOLO Vision 2024 updates https://ultralytics.com/events/yolovision (#15602)

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Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
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Glenn Jocher 2024-08-15 04:22:07 +08:00 committed by GitHub
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4 changed files with 4 additions and 6 deletions
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2
README.md
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@ -1,6 +1,6 @@
<div align="center">
<p>
<a href="https://github.com/ultralytics/assets/releases/tag/v8.2.0" target="_blank">
<a href="https://www.ultralytics.com/events/yolovision" target="_blank">
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="YOLO Vision banner"></a>
</p>

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README.zh-CN.md
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@ -1,6 +1,6 @@
<div align="center">
<p>
<a href="https://github.com/ultralytics/assets/releases/tag/v8.2.0" target="_blank">
<a href="https://www.ultralytics.com/events/yolovision" target="_blank">
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="YOLO Vision banner"></a>
</p>

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docs/en/index.md
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@ -5,7 +5,7 @@ keywords: Ultralytics, YOLOv8, object detection, image segmentation, deep learni
---
<div align="center">
<a href="https://github.com/ultralytics/assets/releases/tag/v8.2.0" target="_blank"><img width="1024%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO banner"></a>
<a href="https://www.ultralytics.com/events/yolovision" target="_blank"><img width="1024%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO banner"></a>
<a href="https://docs.ultralytics.com/zh/">中文</a> |
<a href="https://docs.ultralytics.com/ko/">한국어</a> |
<a href="https://docs.ultralytics.com/ja/">日本語</a> |

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tests/test_cli.py
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@ -84,9 +84,7 @@ def test_fastsam(task="segment", model=WEIGHTS_DIR / "FastSAM-s.pt", data="coco8
new_masks, _ = Predictor.remove_small_regions(everything_results[0].masks.data, min_area=20)
# Run inference with bboxes and points and texts prompt at the same time
results = sam_model(
source, bboxes=[439, 437, 524, 709], points=[[200, 200]], labels=[1], texts="a photo of a dog"
)
sam_model(source, bboxes=[439, 437, 524, 709], points=[[200, 200]], labels=[1], texts="a photo of a dog")
def test_mobilesam():