ultralytics 8.0.54 TFLite export improvements and fixes (#1447)

Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/modes/export.md

@@ -22,11 +22,11 @@ export arguments.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO("yolov8n.pt")  # load an official model
-        model = YOLO("path/to/best.pt")  # load a custom trained
+        model = YOLO('yolov8n.pt')  # load an official model
+        model = YOLO('path/to/best.pt')  # load a custom trained
         
         # Export the model
-        model.export(format="onnx")
+        model.export(format='onnx')
         ```
     === "CLI"
     

docs/modes/track.md

@@ -26,9 +26,9 @@ Use a trained YOLOv8n/YOLOv8n-seg model to run tracker on video streams.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO("yolov8n.pt")  # load an official detection model
-        model = YOLO("yolov8n-seg.pt")  # load an official segmentation model
-        model = YOLO("path/to/best.pt")  # load a custom model
+        model = YOLO('yolov8n.pt')  # load an official detection model
+        model = YOLO('yolov8n-seg.pt')  # load an official segmentation model
+        model = YOLO('path/to/best.pt')  # load a custom model
         
         # Track with the model
         results = model.track(source="https://youtu.be/Zgi9g1ksQHc", show=True) 
@@ -60,7 +60,7 @@ to [predict page](https://docs.ultralytics.com/modes/predict/).
         ```python
         from ultralytics import YOLO
         
-        model = YOLO("yolov8n.pt")
+        model = YOLO('yolov8n.pt')
         results = model.track(source="https://youtu.be/Zgi9g1ksQHc", conf=0.3, iou=0.5, show=True) 
         ```
     === "CLI"
@@ -82,7 +82,7 @@ any configurations(expect the `tracker_type`) you need to.
         ```python
         from ultralytics import YOLO
         
-        model = YOLO("yolov8n.pt")
+        model = YOLO('yolov8n.pt')
         results = model.track(source="https://youtu.be/Zgi9g1ksQHc", tracker='custom_tracker.yaml') 
         ```
     === "CLI"

docs/modes/train.md

@@ -21,16 +21,24 @@ training arguments.
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO("yolov8n.yaml")  # build a new model from scratch
-        model = YOLO("yolov8n.pt")  # load a pretrained model (recommended for training)
+        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)
+        model.train(data='coco128.yaml', epochs=100, imgsz=640)
         ```
     === "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
         ```
 
 ## Arguments

docs/modes/val.md

@@ -21,8 +21,8 @@ training `data` and arguments as model attributes. See Arguments section below f
         from ultralytics import YOLO
         
         # Load a model
-        model = YOLO("yolov8n.pt")  # load an official model
-        model = YOLO("path/to/best.pt")  # load a custom model
+        model = YOLO('yolov8n.pt')  # load an official model
+        model = YOLO('path/to/best.pt')  # load a custom model
         
         # Validate the model
         metrics = model.val()  # no arguments needed, dataset and settings remembered