diff --git a/README.md b/README.md index 3cf2cd8b1..79dd5ff6c 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@

- + YOLO Vision banner

diff --git a/README.zh-CN.md b/README.zh-CN.md index 8641d40e2..6bdc08f2c 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -1,6 +1,6 @@

- + YOLO Vision banner

diff --git a/docs/en/index.md b/docs/en/index.md index 3153378e9..398335ad9 100644 --- a/docs/en/index.md +++ b/docs/en/index.md @@ -5,7 +5,7 @@ keywords: Ultralytics, YOLOv8, object detection, image segmentation, deep learni ---
-Ultralytics YOLO banner +Ultralytics YOLO banner 中文 | 한국어 | 日本語 | diff --git a/tests/test_cli.py b/tests/test_cli.py index 2f3e39ee2..9582dde8f 100644 --- a/tests/test_cli.py +++ b/tests/test_cli.py @@ -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():