ultralytics 8.0.54 TFLite export improvements and fixes (#1447)

Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
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Glenn Jocher 2023-03-16 15:42:44 +01:00 committed by GitHub
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@ -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"