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songjiahao-wq committed Sep 9, 2024
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24 changes: 12 additions & 12 deletions docs/en/modes/predict.md
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Expand Up @@ -385,18 +385,18 @@ Inference arguments:

Visualization arguments:

| Argument | Type | Default | Description |
| ------------- | ------------- | ------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `show` | `bool` | `False` | If `True`, displays the annotated images or videos in a window. Useful for immediate visual feedback during development or testing. |
| `save` | `bool` | `False` | Enables saving of the annotated images or videos to file. Useful for documentation, further analysis, or sharing results. |
| `save_frames` | `bool` | `False` | When processing videos, saves individual frames as images. Useful for extracting specific frames or for detailed frame-by-frame analysis. |
| `save_txt` | `bool` | `False` | Saves detection results in a text file, following the format `[class] [x_center] [y_center] [width] [height] [confidence]`. Useful for integration with other analysis tools. |
| `save_conf` | `bool` | `False` | Includes confidence scores in the saved text files. Enhances the detail available for post-processing and analysis. |
| `save_crop` | `bool` | `False` | Saves cropped images of detections. Useful for dataset augmentation, analysis, or creating focused datasets for specific objects. |
| `show_labels` | `bool` | `True` | Displays labels for each detection in the visual output. Provides immediate understanding of detected objects. |
| `show_conf` | `bool` | `True` | Displays the confidence score for each detection alongside the label. Gives insight into the model's certainty for each detection. |
| `show_boxes` | `bool` | `True` | Draws bounding boxes around detected objects. Essential for visual identification and location of objects in images or video frames. |
| `line_width` | `None or int` | `None` | Specifies the line width of bounding boxes. If `None`, the line width is automatically adjusted based on the image size. Provides visual customization for clarity. |
| Argument | Type | Default | Description |
| ------------- | --------------- | ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `show` | `bool` | `False` | If `True`, displays the annotated images or videos in a window. Useful for immediate visual feedback during development or testing. |
| `save` | `bool` | `False` or `True` | Enables saving of the annotated images or videos to file. Useful for documentation, further analysis, or sharing results. Defaults to True when using CLI & False when used in Python. |
| `save_frames` | `bool` | `False` | When processing videos, saves individual frames as images. Useful for extracting specific frames or for detailed frame-by-frame analysis. |
| `save_txt` | `bool` | `False` | Saves detection results in a text file, following the format `[class] [x_center] [y_center] [width] [height] [confidence]`. Useful for integration with other analysis tools. |
| `save_conf` | `bool` | `False` | Includes confidence scores in the saved text files. Enhances the detail available for post-processing and analysis. |
| `save_crop` | `bool` | `False` | Saves cropped images of detections. Useful for dataset augmentation, analysis, or creating focused datasets for specific objects. |
| `show_labels` | `bool` | `True` | Displays labels for each detection in the visual output. Provides immediate understanding of detected objects. |
| `show_conf` | `bool` | `True` | Displays the confidence score for each detection alongside the label. Gives insight into the model's certainty for each detection. |
| `show_boxes` | `bool` | `True` | Draws bounding boxes around detected objects. Essential for visual identification and location of objects in images or video frames. |
| `line_width` | `None` or `int` | `None` | Specifies the line width of bounding boxes. If `None`, the line width is automatically adjusted based on the image size. Provides visual customization for clarity. |

## Image and Video Formats

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24 changes: 12 additions & 12 deletions docs/en/usage/cfg.md
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Expand Up @@ -171,18 +171,18 @@ Inference arguments:

Visualization arguments:

| Argument | Type | Default | Description |
| ------------- | ------------- | ------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `show` | `bool` | `False` | If `True`, displays the annotated images or videos in a window. Useful for immediate visual feedback during development or testing. |
| `save` | `bool` | `False` | Enables saving of the annotated images or videos to file. Useful for documentation, further analysis, or sharing results. |
| `save_frames` | `bool` | `False` | When processing videos, saves individual frames as images. Useful for extracting specific frames or for detailed frame-by-frame analysis. |
| `save_txt` | `bool` | `False` | Saves detection results in a text file, following the format `[class] [x_center] [y_center] [width] [height] [confidence]`. Useful for integration with other analysis tools. |
| `save_conf` | `bool` | `False` | Includes confidence scores in the saved text files. Enhances the detail available for post-processing and analysis. |
| `save_crop` | `bool` | `False` | Saves cropped images of detections. Useful for dataset augmentation, analysis, or creating focused datasets for specific objects. |
| `show_labels` | `bool` | `True` | Displays labels for each detection in the visual output. Provides immediate understanding of detected objects. |
| `show_conf` | `bool` | `True` | Displays the confidence score for each detection alongside the label. Gives insight into the model's certainty for each detection. |
| `show_boxes` | `bool` | `True` | Draws bounding boxes around detected objects. Essential for visual identification and location of objects in images or video frames. |
| `line_width` | `None or int` | `None` | Specifies the line width of bounding boxes. If `None`, the line width is automatically adjusted based on the image size. Provides visual customization for clarity. |
| Argument | Type | Default | Description |
| ------------- | --------------- | ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `show` | `bool` | `False` | If `True`, displays the annotated images or videos in a window. Useful for immediate visual feedback during development or testing. |
| `save` | `bool` | `False` or `True` | Enables saving of the annotated images or videos to file. Useful for documentation, further analysis, or sharing results. Defaults to True when using CLI & False when used in Python. |
| `save_frames` | `bool` | `False` | When processing videos, saves individual frames as images. Useful for extracting specific frames or for detailed frame-by-frame analysis. |
| `save_txt` | `bool` | `False` | Saves detection results in a text file, following the format `[class] [x_center] [y_center] [width] [height] [confidence]`. Useful for integration with other analysis tools. |
| `save_conf` | `bool` | `False` | Includes confidence scores in the saved text files. Enhances the detail available for post-processing and analysis. |
| `save_crop` | `bool` | `False` | Saves cropped images of detections. Useful for dataset augmentation, analysis, or creating focused datasets for specific objects. |
| `show_labels` | `bool` | `True` | Displays labels for each detection in the visual output. Provides immediate understanding of detected objects. |
| `show_conf` | `bool` | `True` | Displays the confidence score for each detection alongside the label. Gives insight into the model's certainty for each detection. |
| `show_boxes` | `bool` | `True` | Draws bounding boxes around detected objects. Essential for visual identification and location of objects in images or video frames. |
| `line_width` | `None` or `int` | `None` | Specifies the line width of bounding boxes. If `None`, the line width is automatically adjusted based on the image size. Provides visual customization for clarity. |

[Predict Guide](../modes/predict.md){ .md-button }

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3 changes: 2 additions & 1 deletion ultralytics/__init__.py
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@@ -1,6 +1,7 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license

__version__ = "8.2.89"
__version__ = "8.2.90"


import os

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2 changes: 1 addition & 1 deletion ultralytics/engine/exporter.py
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Expand Up @@ -391,7 +391,7 @@ def export_onnx(self, prefix=colorstr("ONNX:")):
"""YOLOv8 ONNX export."""
requirements = ["onnx>=1.12.0"]
if self.args.simplify:
requirements += ["onnxslim>=0.1.31", "onnxruntime" + ("-gpu" if torch.cuda.is_available() else "")]
requirements += ["onnxslim==0.1.32", "onnxruntime" + ("-gpu" if torch.cuda.is_available() else "")]
check_requirements(requirements)
import onnx # noqa

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12 changes: 10 additions & 2 deletions ultralytics/engine/trainer.py
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Expand Up @@ -28,6 +28,7 @@
DEFAULT_CFG,
LOCAL_RANK,
LOGGER,
MACOS,
RANK,
TQDM,
__version__,
Expand Down Expand Up @@ -453,7 +454,10 @@ def _do_train(self, world_size=1):
self.stop |= epoch >= self.epochs # stop if exceeded epochs
self.run_callbacks("on_fit_epoch_end")
gc.collect()
torch.cuda.empty_cache() # clear GPU memory at end of epoch, may help reduce CUDA out of memory errors
if MACOS:
torch.mps.empty_cache() # clear unified memory at end of epoch, may help MPS' management of 'unlimited' virtual memoy
else:
torch.cuda.empty_cache() # clear GPU memory at end of epoch, may help reduce CUDA out of memory errors

# Early Stopping
if RANK != -1: # if DDP training
Expand All @@ -475,7 +479,11 @@ def _do_train(self, world_size=1):
self.plot_metrics()
self.run_callbacks("on_train_end")
gc.collect()
torch.cuda.empty_cache()
if MACOS:
torch.mps.empty_cache()
else:
torch.cuda.empty_cache()

self.run_callbacks("teardown")

def read_results_csv(self):
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