Ultralytics Code Refactor https://ultralytics.com/actions (#14109)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

tests/test_cli.py

@@ -20,7 +20,7 @@ def run(cmd):
 
 
 def test_special_modes():
-    """Test various special command modes of YOLO."""
+    """Test various special command-line modes for YOLO functionality."""
     run("yolo help")
     run("yolo checks")
     run("yolo version")
@@ -30,30 +30,30 @@ def test_special_modes():
 
 @pytest.mark.parametrize("task,model,data", TASK_MODEL_DATA)
 def test_train(task, model, data):
-    """Test YOLO training for a given task, model, and data."""
+    """Test YOLO training for different tasks, models, and datasets."""
     run(f"yolo train {task} model={model} data={data} imgsz=32 epochs=1 cache=disk")
 
 
 @pytest.mark.parametrize("task,model,data", TASK_MODEL_DATA)
 def test_val(task, model, data):
-    """Test YOLO validation for a given task, model, and data."""
+    """Test YOLO validation process for specified task, model, and data using a shell command."""
     run(f"yolo val {task} model={model} data={data} imgsz=32 save_txt save_json")
 
 
 @pytest.mark.parametrize("task,model,data", TASK_MODEL_DATA)
 def test_predict(task, model, data):
-    """Test YOLO prediction on sample assets for a given task and model."""
+    """Test YOLO prediction on provided sample assets for specified task and model."""
     run(f"yolo predict model={model} source={ASSETS} imgsz=32 save save_crop save_txt")
 
 
 @pytest.mark.parametrize("model", MODELS)
 def test_export(model):
-    """Test exporting a YOLO model to different formats."""
+    """Test exporting a YOLO model to TorchScript format."""
     run(f"yolo export model={model} format=torchscript imgsz=32")
 
 
 def test_rtdetr(task="detect", model="yolov8n-rtdetr.yaml", data="coco8.yaml"):
-    """Test the RTDETR functionality with the Ultralytics framework."""
+    """Test the RTDETR functionality within Ultralytics for detection tasks using specified model and data."""
     # Warning: must use imgsz=640 (note also add coma, spaces, fraction=0.25 args to test single-image training)
     run(f"yolo train {task} model={model} data={data} --imgsz= 160 epochs =1, cache = disk fraction=0.25")
     run(f"yolo predict {task} model={model} source={ASSETS / 'bus.jpg'} imgsz=160 save save_crop save_txt")
@@ -61,7 +61,7 @@ def test_rtdetr(task="detect", model="yolov8n-rtdetr.yaml", data="coco8.yaml"):
 
 @pytest.mark.skipif(checks.IS_PYTHON_3_12, reason="MobileSAM with CLIP is not supported in Python 3.12")
 def test_fastsam(task="segment", model=WEIGHTS_DIR / "FastSAM-s.pt", data="coco8-seg.yaml"):
-    """Test FastSAM segmentation functionality within Ultralytics."""
+    """Test FastSAM model for segmenting objects in images using various prompts within Ultralytics."""
     source = ASSETS / "bus.jpg"
 
     run(f"yolo segment val {task} model={model} data={data} imgsz=32")
@@ -99,7 +99,7 @@ def test_fastsam(task="segment", model=WEIGHTS_DIR / "FastSAM-s.pt", data="coco8
 
 
 def test_mobilesam():
-    """Test MobileSAM segmentation functionality using Ultralytics."""
+    """Test MobileSAM segmentation with point prompts using Ultralytics."""
     from ultralytics import SAM
 
     # Load the model