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Start export implementation (#110)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2022-12-29 14:17:14 +01:00
committed by GitHub
parent c1b38428bc
commit 92dad1c1b5
32 changed files with 827 additions and 222 deletions
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8
ultralytics/yolo/utils/__init__.py
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@ -1,4 +1,5 @@
import contextlib
import inspect
import logging.config
import os
import platform
@ -13,6 +14,7 @@ import pandas as pd
# Constants
FILE = Path(__file__).resolve()
ROOT = FILE.parents[2] # YOLO
DEFAULT_CONFIG = ROOT / "yolo/configs/default.yaml"
RANK = int(os.getenv('RANK', -1))
DATASETS_DIR = Path(os.getenv('YOLOv5_DATASETS_DIR', ROOT.parent / 'datasets')) # global datasets directory
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
@ -98,6 +100,12 @@ def is_writeable(dir, test=False):
return False
def get_default_args(func):
# Get func() default arguments
signature = inspect.signature(func)
return {k: v.default for k, v in signature.parameters.items() if v.default is not inspect.Parameter.empty}
def user_config_dir(dir='Ultralytics', env_var='YOLOV5_CONFIG_DIR'):
# Return path of user configuration directory. Prefer environment variable if exists. Make dir if required.
env = os.getenv(env_var)

15
ultralytics/yolo/utils/checks.py
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@ -13,6 +13,7 @@ import torch
from ultralytics.yolo.utils import (AUTOINSTALL, FONT, LOGGER, ROOT, USER_CONFIG_DIR, TryExcept, colorstr, emojis,
is_docker, is_notebook)
from ultralytics.yolo.utils.ops import make_divisible
def is_ascii(s=''):
@ -21,6 +22,18 @@ def is_ascii(s=''):
return len(s.encode().decode('ascii', 'ignore')) == len(s)
def check_imgsz(imgsz, s=32, floor=0):
# Verify image size is a multiple of stride s in each dimension
if isinstance(imgsz, int): # integer i.e. img_size=640
new_size = max(make_divisible(imgsz, int(s)), floor)
else: # list i.e. img_size=[640, 480]
imgsz = list(imgsz) # convert to list if tuple
new_size = [max(make_divisible(x, int(s)), floor) for x in imgsz]
if new_size != imgsz:
LOGGER.warning(f'WARNING ⚠️ --img-size {imgsz} must be multiple of max stride {s}, updating to {new_size}')
return new_size
def check_version(current="0.0.0", minimum="0.0.0", name="version ", pinned=False, hard=False, verbose=False):
# Check version vs. required version
current, minimum = (pkg.parse_version(x) for x in (current, minimum))
@ -93,7 +106,7 @@ def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(), insta
LOGGER.warning(f'{prefix} ❌ {e}')
def check_suffix(file='yolov5s.pt', suffix=('.pt',), msg=''):
def check_suffix(file='yolov8n.pt', suffix=('.pt',), msg=''):
# Check file(s) for acceptable suffix
if file and suffix:
if isinstance(suffix, str):

28
ultralytics/yolo/utils/configs/__init__.py
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@ -1,28 +0,0 @@
from pathlib import Path
from typing import Dict, Union
from omegaconf import DictConfig, OmegaConf
from ultralytics.yolo.utils.configs.hydra_patch import check_config_mismatch
def get_config(config: Union[str, DictConfig], overrides: Union[str, Dict] = {}):
"""
Accepts yaml file name or DictConfig containing experiment configuration.
Returns training args namespace
:param overrides: Overrides str or Dict
:param config: Optional file name or DictConfig object
"""
if isinstance(config, (str, Path)):
config = OmegaConf.load(config)
elif isinstance(config, Dict):
config = OmegaConf.create(config)
# override
if isinstance(overrides, str):
overrides = OmegaConf.load(overrides)
elif isinstance(overrides, Dict):
overrides = OmegaConf.create(overrides)
check_config_mismatch(dict(overrides).keys(), dict(config).keys())
return OmegaConf.merge(config, overrides)

102
ultralytics/yolo/utils/configs/default.yaml
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@ -1,102 +0,0 @@
# YOLO 🚀 by Ultralytics, GPL-3.0 license
# Default training settings and hyperparameters for medium-augmentation COCO training
# Task and Mode
task: "classify" # choices=['detect', 'segment', 'classify', 'init'] # init is a special case
mode: "train" # choice=['train', 'val', 'predict']
# Train settings -------------------------------------------------------------------------------------------------------
model: null # i.e. yolov5s.pt, yolo.yaml
data: null # i.e. coco128.yaml
epochs: 100
batch_size: 16
imgsz: 640
nosave: False
cache: False # True/ram, disk or False
device: '' # cuda device, i.e. 0 or 0,1,2,3 or cpu
workers: 8
project: null
name: null
exist_ok: False
pretrained: False
optimizer: 'SGD' # choices=['SGD', 'Adam', 'AdamW', 'RMSProp']
verbose: False
seed: 0
deterministic: True
local_rank: -1
single_cls: False # train multi-class data as single-class
image_weights: False # use weighted image selection for training
rect: False # support rectangular training
cos_lr: False # use cosine LR scheduler
close_mosaic: 10 # disable mosaic for final 10 epochs
# Segmentation
overlap_mask: True # masks overlap
mask_ratio: 4 # mask downsample ratio
# Classification
dropout: False # use dropout
resume: False
# Val/Test settings ----------------------------------------------------------------------------------------------------
noval: False
save_json: False
save_hybrid: False
conf_thres: 0.001
iou_thres: 0.7
max_det: 300
half: True
dnn: False # use OpenCV DNN for ONNX inference
plots: True
# Prediction settings:
source: "ultralytics/assets/"
view_img: False
save_txt: False
save_conf: False
save_crop: False
hide_labels: False # hide labels
hide_conf: False
vid_stride: 1 # video frame-rate stride
line_thickness: 3 # bounding box thickness (pixels)
update: False # Update all models
visualize: False
augment: False
agnostic_nms: False # class-agnostic NMS
retina_masks: False
# Hyperparameters ------------------------------------------------------------------------------------------------------
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
lrf: 0.01 # final OneCycleLR learning rate (lr0 * lrf)
momentum: 0.937 # SGD momentum/Adam beta1
weight_decay: 0.0005 # optimizer weight decay 5e-4
warmup_epochs: 3.0 # warmup epochs (fractions ok)
warmup_momentum: 0.8 # warmup initial momentum
warmup_bias_lr: 0.1 # warmup initial bias lr
box: 7.5 # box loss gain
cls: 0.5 # cls loss gain (scale with pixels)
dfl: 1.5 # dfl loss gain
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
label_smoothing: 0.0
nbs: 64 # nominal batch size
hsv_h: 0.015 # image HSV-Hue augmentation (fraction)
hsv_s: 0.7 # image HSV-Saturation augmentation (fraction)
hsv_v: 0.4 # image HSV-Value augmentation (fraction)
degrees: 0.0 # image rotation (+/- deg)
translate: 0.1 # image translation (+/- fraction)
scale: 0.5 # image scale (+/- gain)
shear: 0.0 # image shear (+/- deg)
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
flipud: 0.0 # image flip up-down (probability)
fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.0 # image mixup (probability)
copy_paste: 0.0 # segment copy-paste (probability)
# For debugging. Don't change
v5loader: True
# Hydra configs --------------------------------------------------------------------------------------------------------
hydra:
output_subdir: null # disable hydra directory creation
run:
dir: .

79
ultralytics/yolo/utils/configs/hydra_patch.py
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@ -1,79 +0,0 @@
import sys
from difflib import get_close_matches
from textwrap import dedent
import hydra
from hydra.errors import ConfigCompositionException
from omegaconf import OmegaConf, open_dict
from omegaconf.errors import ConfigAttributeError, ConfigKeyError, OmegaConfBaseException
from ultralytics.yolo.utils import LOGGER, colorstr
def override_config(overrides, cfg):
override_keys = [override.key_or_group for override in overrides]
check_config_mismatch(override_keys, cfg.keys())
for override in overrides:
if override.package is not None:
raise ConfigCompositionException(f"Override {override.input_line} looks like a config group"
f" override, but config group '{override.key_or_group}' does not"
" exist.")
key = override.key_or_group
value = override.value()
try:
if override.is_delete():
config_val = OmegaConf.select(cfg, key, throw_on_missing=False)
if config_val is None:
raise ConfigCompositionException(f"Could not delete from config. '{override.key_or_group}'"
" does not exist.")
elif value is not None and value != config_val:
raise ConfigCompositionException("Could not delete from config. The value of"
f" '{override.key_or_group}' is {config_val} and not"
f" {value}.")
last_dot = key.rfind(".")
with open_dict(cfg):
if last_dot == -1:
del cfg[key]
else:
node = OmegaConf.select(cfg, key[0:last_dot])
del node[key[last_dot + 1:]]
elif override.is_add():
if OmegaConf.select(cfg, key, throw_on_missing=False) is None or isinstance(value, (dict, list)):
OmegaConf.update(cfg, key, value, merge=True, force_add=True)
else:
assert override.input_line is not None
raise ConfigCompositionException(
dedent(f"""\
Could not append to config. An item is already at '{override.key_or_group}'.
Either remove + prefix: '{override.input_line[1:]}'
Or add a second + to add or override '{override.key_or_group}': '+{override.input_line}'
"""))
elif override.is_force_add():
OmegaConf.update(cfg, key, value, merge=True, force_add=True)
else:
try:
OmegaConf.update(cfg, key, value, merge=True)
except (ConfigAttributeError, ConfigKeyError) as ex:
raise ConfigCompositionException(f"Could not override '{override.key_or_group}'."
f"\nTo append to your config use +{override.input_line}") from ex
except OmegaConfBaseException as ex:
raise ConfigCompositionException(f"Error merging override {override.input_line}").with_traceback(
sys.exc_info()[2]) from ex
def check_config_mismatch(overrides, cfg):
mismatched = []
for option in overrides:
if option not in cfg and 'hydra.' not in option:
mismatched.append(option)
for option in mismatched:
LOGGER.info(f"{colorstr(option)} is not a valid key. Similar keys: {get_close_matches(option, cfg, 3, 0.6)}")
if mismatched:
exit()
hydra._internal.config_loader_impl.ConfigLoaderImpl._apply_overrides_to_config = override_config

2
ultralytics/yolo/utils/downloads.py
View File

@ -49,7 +49,7 @@ def attempt_download(file, repo='ultralytics/yolov5', release='v6.2'):
# Attempt file download from GitHub release assets if not found locally. release = 'latest', 'v6.2', etc.
def github_assets(repository, version='latest'):
# Return GitHub repo tag and assets (i.e. ['yolov5s.pt', 'yolov5m.pt', ...])
# Return GitHub repo tag and assets (i.e. ['yolov8n.pt', 'yolov5m.pt', ...])
if version != 'latest':
version = f'tags/{version}' # i.e. tags/v6.2
response = requests.get(f'https://api.github.com/repos/{repository}/releases/{version}').json() # github api

23
ultralytics/yolo/utils/files.py
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@ -1,6 +1,7 @@
import contextlib
import glob
import os
import urllib
from datetime import datetime
from pathlib import Path
from zipfile import ZipFile
@ -43,7 +44,7 @@ def increment_path(path, exist_ok=False, sep='', mkdir=False):
return path
def save_yaml(file='data.yaml', data=None):
def yaml_save(file='data.yaml', data=None):
# Single-line safe yaml saving
with open(file, 'w') as f:
yaml.safe_dump({k: str(v) if isinstance(v, Path) else v for k, v in data.items()}, f, sort_keys=False)
@ -52,7 +53,7 @@ def save_yaml(file='data.yaml', data=None):
def yaml_load(file='data.yaml'):
# Single-line safe yaml loading
with open(file, errors='ignore') as f:
return yaml.safe_load(f)
return {**yaml.safe_load(f), 'yaml_file': file} # add YAML filename to dict and return
def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX')):
@ -77,6 +78,24 @@ def file_date(path=__file__):
return f'{t.year}-{t.month}-{t.day}'
def file_size(path):
# Return file/dir size (MB)
mb = 1 << 20 # bytes to MiB (1024 ** 2)
path = Path(path)
if path.is_file():
return path.stat().st_size / mb
elif path.is_dir():
return sum(f.stat().st_size for f in path.glob('**/*') if f.is_file()) / mb
else:
return 0.0
def url2file(url):
# Convert URL to filename, i.e. https://url.com/file.txt?auth -> file.txt
url = str(Path(url)).replace(':/', '://') # Pathlib turns :// -> :/
return Path(urllib.parse.unquote(url)).name.split('?')[0] # '%2F' to '/', split https://url.com/file.txt?auth
def get_latest_run(search_dir='.'):
# Return path to most recent 'last.pt' in /runs (i.e. to --resume from)
last_list = glob.glob(f'{search_dir}/**/last*.pt', recursive=True)

2
ultralytics/yolo/utils/ops.py
View File

@ -135,7 +135,7 @@ def non_max_suppression(
for xi, x in enumerate(prediction): # image index, image inference
# Apply constraints
# x[((x[:, 2:4] < min_wh) | (x[:, 2:4] > max_wh)).any(1), 4] = 0 # width-height
x = x.T[xc[xi]] # confidence
x = x.transpose(0, -1)[xc[xi]] # confidence
# Cat apriori labels if autolabelling
if labels and len(labels[xi]):

4
ultralytics/yolo/utils/torch_utils.py
View File

@ -135,8 +135,8 @@ def model_info(model, verbose=False, imgsz=640):
flops = get_flops(model, imgsz)
fs = f', {flops:.1f} GFLOPs' if flops else ''
name = Path(model.yaml_file).stem.replace('yolov5', 'YOLOv5') if hasattr(model, 'yaml_file') else 'Model'
LOGGER.info(f"{name} summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}")
m = Path(getattr(model, 'yaml_file', '') or model.yaml.get('yaml_file', '')).stem.replace('yolo', 'YOLO') or 'Model'
LOGGER.info(f"{m} summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}")
def get_num_params(model):