退购1.1定位算法

tests/test_cli.py

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+# Ultralytics YOLO 🚀, AGPL-3.0 license
+
+import subprocess
+from pathlib import Path
+
+from ultralytics.yolo.utils import LINUX, ONLINE, ROOT, SETTINGS
+
+MODEL = Path(SETTINGS['weights_dir']) / 'yolov8n'
+CFG = 'yolov8n'
+
+
+def run(cmd):
+    # Run a subprocess command with check=True
+    subprocess.run(cmd.split(), check=True)
+
+
+def test_special_modes():
+    run('yolo checks')
+    run('yolo settings')
+    run('yolo help')
+
+
+# Train checks ---------------------------------------------------------------------------------------------------------
+def test_train_det():
+    run(f'yolo train detect model={CFG}.yaml data=coco8.yaml imgsz=32 epochs=1 v5loader')
+
+
+def test_train_seg():
+    run(f'yolo train segment model={CFG}-seg.yaml data=coco8-seg.yaml imgsz=32 epochs=1')
+
+
+def test_train_cls():
+    run(f'yolo train classify model={CFG}-cls.yaml data=imagenet10 imgsz=32 epochs=1')
+
+
+def test_train_pose():
+    run(f'yolo train pose model={CFG}-pose.yaml data=coco8-pose.yaml imgsz=32 epochs=1')
+
+
+# Val checks -----------------------------------------------------------------------------------------------------------
+def test_val_detect():
+    run(f'yolo val detect model={MODEL}.pt data=coco8.yaml imgsz=32')
+
+
+def test_val_segment():
+    run(f'yolo val segment model={MODEL}-seg.pt data=coco8-seg.yaml imgsz=32')
+
+
+def test_val_classify():
+    run(f'yolo val classify model={MODEL}-cls.pt data=imagenet10 imgsz=32')
+
+
+def test_val_pose():
+    run(f'yolo val pose model={MODEL}-pose.pt data=coco8-pose.yaml imgsz=32')
+
+
+# Predict checks -------------------------------------------------------------------------------------------------------
+def test_predict_detect():
+    run(f"yolo predict model={MODEL}.pt source={ROOT / 'assets'} imgsz=32 save save_crop save_txt")
+    if ONLINE:
+        run(f'yolo predict model={MODEL}.pt source=https://ultralytics.com/images/bus.jpg imgsz=32')
+        run(f'yolo predict model={MODEL}.pt source=https://ultralytics.com/assets/decelera_landscape_min.mov imgsz=32')
+        run(f'yolo predict model={MODEL}.pt source=https://ultralytics.com/assets/decelera_portrait_min.mov imgsz=32')
+
+
+def test_predict_segment():
+    run(f"yolo predict model={MODEL}-seg.pt source={ROOT / 'assets'} imgsz=32 save save_txt")
+
+
+def test_predict_classify():
+    run(f"yolo predict model={MODEL}-cls.pt source={ROOT / 'assets'} imgsz=32 save save_txt")
+
+
+def test_predict_pose():
+    run(f"yolo predict model={MODEL}-pose.pt source={ROOT / 'assets'} imgsz=32 save save_txt")
+
+
+# Export checks --------------------------------------------------------------------------------------------------------
+def test_export_detect_torchscript():
+    run(f'yolo export model={MODEL}.pt format=torchscript')
+
+
+def test_export_segment_torchscript():
+    run(f'yolo export model={MODEL}-seg.pt format=torchscript')
+
+
+def test_export_classify_torchscript():
+    run(f'yolo export model={MODEL}-cls.pt format=torchscript')
+
+
+def test_export_classify_pose():
+    run(f'yolo export model={MODEL}-pose.pt format=torchscript')
+
+
+def test_export_detect_edgetpu(enabled=False):
+    if enabled and LINUX:
+        run(f'yolo export model={MODEL}.pt format=edgetpu')