Improved CLI error reporting for users (#458)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-01-18 09:16:16 +01:00
committed by GitHub
parent db26ccba94
commit cc3c774bde
6 changed files with 275 additions and 115 deletions

View File

@ -4,13 +4,53 @@ import argparse
import shutil
from pathlib import Path
from hydra import compose, initialize
from ultralytics import hub, yolo
from ultralytics.yolo.utils import DEFAULT_CONFIG, HELP_MSG, LOGGER, PREFIX, print_settings, yaml_load
from ultralytics import __version__, yolo
from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, PREFIX, checks, print_settings, yaml_load
DIR = Path(__file__).parent
CLI_HELP_MSG = \
"""
YOLOv8 CLI Usage examples:
1. Install the ultralytics package:
pip install ultralytics
2. Train, Val, Predict and Export using 'yolo' commands of the form:
yolo TASK MODE ARGS
Where TASK (optional) is one of [detect, segment, classify]
MODE (required) is one of [train, val, predict, export]
ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
For a full list of available ARGS see https://docs.ultralytics.com/config.
Train a detection model for 10 epochs with an initial learning_rate of 0.01
yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01
Predict a YouTube video using a pretrained segmentation model at image size 320:
yolo segment predict model=yolov8n-seg.pt source=https://youtu.be/Zgi9g1ksQHc imgsz=320
Validate a pretrained detection model at batch-size 1 and image size 640:
yolo detect val model=yolov8n.pt data=coco128.yaml batch=1 imgsz=640
Export a YOLOv8n 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
3. Run special commands:
yolo help
yolo checks
yolo version
yolo settings
yolo copy-config
Docs: https://docs.ultralytics.com/cli
Community: https://community.ultralytics.com
GitHub: https://github.com/ultralytics/ultralytics
"""
def cli(cfg):
"""
@ -28,20 +68,16 @@ def cli(cfg):
task, mode = cfg.task.lower(), cfg.mode.lower()
# Mapping from task to module
task_module_map = {"detect": yolo.v8.detect, "segment": yolo.v8.segment, "classify": yolo.v8.classify}
module = task_module_map.get(task)
tasks = {"detect": yolo.v8.detect, "segment": yolo.v8.segment, "classify": yolo.v8.classify}
module = tasks.get(task)
if not module:
raise SyntaxError(f"task not recognized. Choices are {', '.join(task_module_map.keys())}")
raise SyntaxError(f"yolo task={task} is invalid. Valid tasks are: {', '.join(tasks.keys())}\n{CLI_HELP_MSG}")
# Mapping from mode to function
mode_func_map = {
"train": module.train,
"val": module.val,
"predict": module.predict,
"export": yolo.engine.exporter.export}
func = mode_func_map.get(mode)
modes = {"train": module.train, "val": module.val, "predict": module.predict, "export": yolo.engine.exporter.export}
func = modes.get(mode)
if not func:
raise SyntaxError(f"mode not recognized. Choices are {', '.join(mode_func_map.keys())}")
raise SyntaxError(f"yolo mode={mode} is invalid. Valid modes are: {', '.join(modes.keys())}\n{CLI_HELP_MSG}")
func(cfg)
@ -68,8 +104,9 @@ def entrypoint():
tasks = 'detect', 'segment', 'classify'
modes = 'train', 'val', 'predict', 'export'
special_modes = {
'checks': hub.checks,
'help': lambda: LOGGER.info(HELP_MSG),
'help': lambda: LOGGER.info(CLI_HELP_MSG),
'checks': checks.check_yolo,
'version': lambda: LOGGER.info(__version__),
'settings': print_settings,
'copy-config': copy_default_config}
@ -87,8 +124,17 @@ def entrypoint():
return
elif a in defaults and defaults[a] is False:
overrides.append(f'{a}=True') # auto-True for default False args, i.e. yolo show
elif a in defaults:
raise SyntaxError(f"'{a}' is a valid YOLO argument but is missing an '=' sign to set its value, "
f"i.e. try '{a}={defaults[a]}'"
f"\n{CLI_HELP_MSG}")
else:
raise (SyntaxError(f"'{a}' is not a valid yolo argument\n{HELP_MSG}"))
raise SyntaxError(
f"'{a}' is not a valid YOLO argument. For a full list of valid arguments see "
f"https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/configs/default.yaml"
f"\n{CLI_HELP_MSG}")
from hydra import compose, initialize
with initialize(version_base=None, config_path=str(DEFAULT_CONFIG.parent.relative_to(DIR)), job_name="YOLO"):
cfg = compose(config_name=DEFAULT_CONFIG.name, overrides=overrides)

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@ -3,7 +3,9 @@
import glob
import inspect
import math
import os
import platform
import shutil
import urllib
from pathlib import Path
from subprocess import check_output
@ -12,10 +14,12 @@ from typing import Optional
import cv2
import numpy as np
import pkg_resources as pkg
import psutil
import torch
from IPython import display
from ultralytics.yolo.utils import (AUTOINSTALL, FONT, LOGGER, ROOT, USER_CONFIG_DIR, TryExcept, colorstr, emojis,
is_docker, is_jupyter_notebook)
is_colab, is_docker, is_jupyter_notebook)
def is_ascii(s) -> bool:
@ -245,6 +249,26 @@ def check_imshow(warn=False):
return False
def check_yolo(verbose=True):
from ultralytics.yolo.utils.torch_utils import select_device
if is_colab():
shutil.rmtree('sample_data', ignore_errors=True) # remove colab /sample_data directory
if verbose:
# System info
gib = 1 << 30 # bytes per GiB
ram = psutil.virtual_memory().total
total, used, free = shutil.disk_usage("/")
display.clear_output()
s = f'({os.cpu_count()} CPUs, {ram / gib:.1f} GB RAM, {(total - free) / gib:.1f}/{total / gib:.1f} GB disk)'
else:
s = ''
select_device(newline=False)
LOGGER.info(f'Setup complete ✅ {s}')
def git_describe(path=ROOT): # path must be a directory
# Return human-readable git description, i.e. v5.0-5-g3e25f1e https://git-scm.com/docs/git-describe
try: