ultralytics 8.0.55 unified YOLOv8 model YAMLs (#1475)

docs/tasks/classify.md

@@ -26,16 +26,25 @@ see the [Configuration](../usage/cfg.md) page.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO('yolov8n-cls.yaml')  # build a new model from scratch
+        model = YOLO('yolov8n-cls.yaml')  # build a new model from YAML
         model = YOLO('yolov8n-cls.pt')  # load a pretrained model (recommended for training)
+        model = YOLO('yolov8n-cls.yaml').load('yolov8n-cls.pt')  # build from YAML and transfer weights
         
         # Train the model
         model.train(data='mnist160', epochs=100, imgsz=64)
         ```
+
     === "CLI"
-    
+
         ```bash
+        # Build a new model from YAML and start training from scratch
+        yolo classify train data=mnist160 model=yolov8n-cls.yaml epochs=100 imgsz=64
+
+        # Start training from a pretrained *.pt model
         yolo classify train data=mnist160 model=yolov8n-cls.pt epochs=100 imgsz=64
+
+        # Build a new model from YAML, transfer pretrained weights to it and start training
+        yolo classify train data=mnist160 model=yolov8n-cls.yaml pretrained=yolov8n-cls.pt epochs=100 imgsz=64
         ```
 
 ## Val

docs/tasks/detect.md

@@ -26,8 +26,9 @@ the [Configuration](../usage/cfg.md) page.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO('yolov8n.yaml')  # build a new model from scratch
+        model = YOLO('yolov8n.yaml')  # build a new model from YAML
         model = YOLO('yolov8n.pt')  # load a pretrained model (recommended for training)
+        model = YOLO('yolov8n.yaml').load('yolov8n.pt')  # build from YAML and transfer weights
         
         # Train the model
         model.train(data='coco128.yaml', epochs=100, imgsz=640)
@@ -35,7 +36,14 @@ the [Configuration](../usage/cfg.md) page.
     === "CLI"
     
         ```bash
+        # Build a new model from YAML and start training from scratch
+        yolo detect train data=coco128.yaml model=yolov8n.yaml epochs=100 imgsz=640
+
+        # Start training from a pretrained *.pt model
         yolo detect train data=coco128.yaml model=yolov8n.pt epochs=100 imgsz=640
+
+        # Build a new model from YAML, transfer pretrained weights to it and start training
+        yolo detect train data=coco128.yaml model=yolov8n.yaml pretrained=yolov8n.pt epochs=100 imgsz=640
         ```
 
 ## Val

docs/tasks/keypoints.md

@@ -28,8 +28,9 @@ train an OpenPose model on a custom dataset, see the OpenPose Training page.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO('yolov8n.yaml')  # build a new model from scratch
+        model = YOLO('yolov8n.yaml')  # build a new model from YAML
         model = YOLO('yolov8n.pt')  # load a pretrained model (recommended for training)
+        model = YOLO('yolov8n.yaml').load('yolov8n.pt')  # build from YAML and transfer weights
         
         # Train the model
         model.train(data='coco128.yaml', epochs=100, imgsz=640)
@@ -37,7 +38,14 @@ train an OpenPose model on a custom dataset, see the OpenPose Training page.
     === "CLI"
     
         ```bash
+        # Build a new model from YAML and start training from scratch
+        yolo detect train data=coco128.yaml model=yolov8n.yaml epochs=100 imgsz=640
+
+        # Start training from a pretrained *.pt model
         yolo detect train data=coco128.yaml model=yolov8n.pt epochs=100 imgsz=640
+
+        # Build a new model from YAML, transfer pretrained weights to it and start training
+        yolo detect train data=coco128.yaml model=yolov8n.yaml pretrained=yolov8n.pt epochs=100 imgsz=640
         ```
 
 ## Val TODO

docs/tasks/segment.md

@@ -26,8 +26,9 @@ arguments see the [Configuration](../usage/cfg.md) page.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO('yolov8n-seg.yaml')  # build a new model from scratch
+        model = YOLO('yolov8n-seg.yaml')  # build a new model from YAML
         model = YOLO('yolov8n-seg.pt')  # load a pretrained model (recommended for training)
+        model = YOLO('yolov8n-seg.yaml').load('yolov8n.pt')  # build from YAML and transfer weights
         
         # Train the model
         model.train(data='coco128-seg.yaml', epochs=100, imgsz=640)
@@ -35,7 +36,14 @@ arguments see the [Configuration](../usage/cfg.md) page.
     === "CLI"
     
         ```bash
+        # Build a new model from YAML and start training from scratch
+        yolo segment train data=coco128-seg.yaml model=yolov8n-seg.yaml epochs=100 imgsz=640
+
+        # Start training from a pretrained *.pt model
         yolo segment train data=coco128-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640
+
+        # Build a new model from YAML, transfer pretrained weights to it and start training
+        yolo segment train data=coco128-seg.yaml model=yolov8n-seg.yaml pretrained=yolov8n-seg.pt epochs=100 imgsz=640
         ```
 
 ## Val

docs/usage/cfg.md

@@ -143,7 +143,7 @@ given task.
 | `agnostic_nms`   | `False`                | class-agnostic NMS                                       |
 | `retina_masks`   | `False`                | use high-resolution segmentation masks                   |
 | `classes`        | `None`                 | filter results by class, i.e. class=0, or class=[0,2,3]  |
-| `box`            | `True`                 | Show boxes in segmentation predictions                   |
+| `boxes`          | `True`                 | Show boxes in segmentation predictions                   |
 
 ### Validation