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Fix and add missing infos about available CLI TASK commands in docs and code comments (#16697)

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Jan Knobloch 2024-10-05 00:23:06 +02:00 • committed by GitHub
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6
docs/en/usage/cfg.md
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@ -41,8 +41,8 @@ Ultralytics commands use the following syntax:
Where: Where:
- `TASK` (optional) is one of ([detect](../tasks/detect.md), [segment](../tasks/segment.md), [classify](../tasks/classify.md), [pose](../tasks/pose.md)) - `TASK` (optional) is one of ([detect](../tasks/detect.md), [segment](../tasks/segment.md), [classify](../tasks/classify.md), [pose](../tasks/pose.md), [obb](../tasks/obb.md))
- `MODE` (required) is one of ([train](../modes/train.md), [val](../modes/val.md), [predict](../modes/predict.md), [export](../modes/export.md), [track](../modes/track.md)) - `MODE` (required) is one of ([train](../modes/train.md), [val](../modes/val.md), [predict](../modes/predict.md), [export](../modes/export.md), [track](../modes/track.md), [benchmark](../modes/benchmark.md))
- `ARGS` (optional) are `arg=value` pairs like `imgsz=640` that override defaults. - `ARGS` (optional) are `arg=value` pairs like `imgsz=640` that override defaults.
Default `ARG` values are defined on this page from the `cfg/defaults.yaml` [file](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml). Default `ARG` values are defined on this page from the `cfg/defaults.yaml` [file](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/default.yaml).
@ -59,7 +59,7 @@ YOLO models can be used for a variety of tasks, including detection, segmentatio
| Argument | Default | Description | | Argument | Default | Description |
| -------- | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | -------- | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `task` | `'detect'` | Specifies the YOLO task to be executed. Options include `detect` for [object detection](https://www.ultralytics.com/glossary/object-detection), `segment` for segmentation, `classify` for classification, `pose` for pose estimation and `OBB` for oriented bounding boxes. Each task is tailored to specific types of output and problems within image and video analysis. | | `task` | `'detect'` | Specifies the YOLO task to be executed. Options include `detect` for [object detection](https://www.ultralytics.com/glossary/object-detection), `segment` for segmentation, `classify` for classification, `pose` for pose estimation and `obb` for oriented bounding boxes. Each task is tailored to specific types of output and problems within image and video analysis. |
[Tasks Guide](../tasks/index.md){ .md-button } [Tasks Guide](../tasks/index.md){ .md-button }

2
ultralytics/cfg/default.yaml
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@ -1,7 +1,7 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Default training settings and hyperparameters for medium-augmentation COCO training # Default training settings and hyperparameters for medium-augmentation COCO training
task: detect # (str) YOLO task, i.e. detect, segment, classify, pose task: detect # (str) YOLO task, i.e. detect, segment, classify, pose, obb
mode: train # (str) YOLO mode, i.e. train, val, predict, export, track, benchmark mode: train # (str) YOLO mode, i.e. train, val, predict, export, track, benchmark
# Train settings ------------------------------------------------------------------------------------------------------- # Train settings -------------------------------------------------------------------------------------------------------

4
ultralytics/data/utils.py
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@ -452,12 +452,12 @@ class HUBDatasetStats:
path = Path(path).resolve() path = Path(path).resolve()
LOGGER.info(f"Starting HUB dataset checks for {path}....") LOGGER.info(f"Starting HUB dataset checks for {path}....")
self.task = task # detect, segment, pose, classify self.task = task # detect, segment, pose, classify, obb
if self.task == "classify": if self.task == "classify":
unzip_dir = unzip_file(path) unzip_dir = unzip_file(path)
data = check_cls_dataset(unzip_dir) data = check_cls_dataset(unzip_dir)
data["path"] = unzip_dir data["path"] = unzip_dir
else: # detect, segment, pose else: # detect, segment, pose, obb
_, data_dir, yaml_path = self._unzip(Path(path)) _, data_dir, yaml_path = self._unzip(Path(path))
try: try:
# Load YAML with checks # Load YAML with checks

16
ultralytics/utils/__init__.py
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@ -61,8 +61,8 @@ HELP_MSG = """
from ultralytics import YOLO from ultralytics import YOLO
# Load a model # Load a model
model = YOLO("yolov8n.yaml") # build a new model from scratch model = YOLO("yolo11n.yaml") # build a new model from scratch
model = YOLO("yolov8n.pt") # load a pretrained model (recommended for training) model = YOLO("yolo11n.pt") # load a pretrained model (recommended for training)
# Use the model # Use the model
results = model.train(data="coco8.yaml", epochs=3) # train the model results = model.train(data="coco8.yaml", epochs=3) # train the model
@ -77,21 +77,21 @@ HELP_MSG = """
yolo TASK MODE ARGS yolo TASK MODE ARGS
Where TASK (optional) is one of [detect, segment, classify, pose, obb] Where TASK (optional) is one of [detect, segment, classify, pose, obb]
MODE (required) is one of [train, val, predict, export, benchmark] MODE (required) is one of [train, val, predict, export, track, benchmark]
ARGS (optional) are any number of custom "arg=value" pairs like "imgsz=320" that override defaults. ARGS (optional) are any number of custom "arg=value" pairs like "imgsz=320" that override defaults.
See all ARGS at https://docs.ultralytics.com/usage/cfg or with "yolo cfg" See all ARGS at https://docs.ultralytics.com/usage/cfg or with "yolo cfg"
- Train a detection model for 10 epochs with an initial learning_rate of 0.01 - Train a detection model for 10 epochs with an initial learning_rate of 0.01
yolo detect train data=coco8.yaml model=yolov8n.pt epochs=10 lr0=0.01 yolo detect train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01
- Predict a YouTube video using a pretrained segmentation model at image size 320: - Predict a YouTube video using a pretrained segmentation model at image size 320:
yolo segment predict model=yolov8n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320 yolo segment predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320
- Val a pretrained detection model at batch-size 1 and image size 640: - Val a pretrained detection model at batch-size 1 and image size 640:
yolo detect val model=yolov8n.pt data=coco8.yaml batch=1 imgsz=640 yolo detect val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640
- Export a YOLOv8n classification model to ONNX format at image size 224 by 128 (no TASK required) - Export a YOLO11n classification model to ONNX format at image size 224 by 128 (no TASK required)
yolo export model=yolov8n-cls.pt format=onnx imgsz=224,128 yolo export model=yolo11n-cls.pt format=onnx imgsz=224,128
- Run special commands: - Run special commands:
yolo help yolo help