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/usage/callbacks.md

@@ -17,7 +17,7 @@ def on_predict_batch_end(predictor):
     im0s = im0s if isinstance(im0s, list) else [im0s]
     predictor.results = zip(predictor.results, im0s)
 
-model = YOLO(f"yolov8n.pt")
+model = YOLO(f'yolov8n.pt')
 model.add_callback("on_predict_batch_end", on_predict_batch_end)
 for (result, frame) in model.track/predict():
     pass

docs/usage/cli.md

@@ -59,8 +59,8 @@ Use a trained YOLOv8n model to run predictions on images.
 !!! example ""
 
       ```bash
-      yolo detect predict model=yolov8n.pt source="https://ultralytics.com/images/bus.jpg"  # predict with official model
-      yolo detect predict model=path/to/best.pt source="https://ultralytics.com/images/bus.jpg"  # predict with custom model
+      yolo detect predict model=yolov8n.pt source='https://ultralytics.com/images/bus.jpg'  # predict with official model
+      yolo detect predict model=path/to/best.pt source='https://ultralytics.com/images/bus.jpg'  # predict with custom model
       ```
 
 ## Export

docs/usage/python.md

@@ -6,7 +6,7 @@ The simplest way of simply using YOLOv8 directly in a Python environment.
         ```python
         from ultralytics import YOLO
 
-        model = YOLO("yolov8n.pt") # pass any model type
+        model = YOLO('yolov8n.pt') # pass any model type
         model.train(epochs=5)
         ```
 
@@ -14,8 +14,8 @@ The simplest way of simply using YOLOv8 directly in a Python environment.
         ```python
         from ultralytics import YOLO
 
-        model = YOLO("yolov8n.yaml")
-        model.train(data="coco128.yaml", epochs=5)
+        model = YOLO('yolov8n.yaml')
+        model.train(data='coco128.yaml', epochs=5)
         ```
 
     === "Resume"
@@ -31,8 +31,8 @@ The simplest way of simply using YOLOv8 directly in a Python environment.
         ```python
           from ultralytics import YOLO
 
-          model = YOLO("yolov8n.yaml")
-          model.train(data="coco128.yaml", epochs=5)
+          model = YOLO('yolov8n.yaml')
+          model.train(data='coco128.yaml', epochs=5)
           model.val()  # It'll automatically evaluate the data you trained.
         ```
 
@@ -44,7 +44,7 @@ The simplest way of simply using YOLOv8 directly in a Python environment.
           # It'll use the data yaml file in model.pt if you don't set data.
           model.val()
           # or you can set the data you want to val
-          model.val(data="coco128.yaml")
+          model.val(data='coco128.yaml')
         ```
 
 !!! example "Predict"