Merge develop branch into master (#3518)

* update ci-testing.yml (#3322)

* update ci-testing.yml

* update greetings.yml

* bring back os matrix

* update ci-testing.yml (#3322)

* update ci-testing.yml

* update greetings.yml

* bring back os matrix

* Enable direct `--weights URL` definition (#3373)

* Enable direct `--weights URL` definition

@KalenMike this PR will enable direct --weights URL definition. Example use case:
```
python train.py --weights https://storage.googleapis.com/bucket/dir/model.pt
```

* cleanup

* bug fixes

* weights = attempt_download(weights)

* Update experimental.py

* Update hubconf.py

* return bug fix

* comment mirror

* min_bytes

* Update tutorial.ipynb (#3368)

add Open in Kaggle badge

* `cv2.imread(img, -1)` for IMREAD_UNCHANGED (#3379)

* Update datasets.py

* comment

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* COCO evolution fix (#3388)

* COCO evolution fix

* cleanup

* update print

* print fix

* Create `is_pip()` function (#3391)

Returns `True` if file is part of pip package. Useful for contextual behavior modification.

```python
def is_pip():
    # Is file in a pip package?
    return 'site-packages' in Path(__file__).absolute().parts
```

* Revert "`cv2.imread(img, -1)` for IMREAD_UNCHANGED (#3379)" (#3395)

This reverts commit 21a9607e00.

* Update FLOPs description (#3422)

* Update README.md

* Changing FLOPS to FLOPs.

Co-authored-by: BuildTools <unconfigured@null.spigotmc.org>

* Parse URL authentication (#3424)

* Parse URL authentication

* urllib.parse.unquote()

* improved error handling

* improved error handling

* remove %3F

* update check_file()

* Add FLOPs title to table (#3453)

* Suppress jit trace warning + graph once (#3454)

* Suppress jit trace warning + graph once

Suppress harmless jit trace warning on TensorBoard add_graph call. Also fix multiple add_graph() calls bug, now only on batch 0.

* Update train.py

* Update MixUp augmentation `alpha=beta=32.0` (#3455)

Per VOC empirical results https://github.com/ultralytics/yolov5/issues/3380#issuecomment-853001307 by @developer0hye

* Add `timeout()` class (#3460)

* Add `timeout()` class

* rearrange order

* Faster HSV augmentation (#3462)

remove datatype conversion process that can be skipped

* Add `check_git_status()` 5 second timeout (#3464)

* Add check_git_status() 5 second timeout

This should prevent the SSH Git bug that we were discussing @KalenMike

* cleanup

* replace timeout with check_output built-in timeout

* Improved `check_requirements()` offline-handling (#3466)

Improve robustness of `check_requirements()` function to offline environments (do not attempt pip installs when offline).

* Add `output_names` argument for ONNX export with dynamic axes (#3456)

* Add output names & dynamic axes for onnx export

Add output_names and dynamic_axes names for all outputs in torch.onnx.export. The first four outputs of the model will have names output0, output1, output2, output3

* use first output only + cleanup

Co-authored-by: Samridha Shrestha <samridha.shrestha@g42.ai>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Revert FP16 `test.py` and `detect.py` inference to FP32 default (#3423)

* fixed inference bug ,while use half precision

* replace --use-half with --half

* replace space and PEP8 in detect.py

* PEP8 detect.py

* update --half help comment

* Update test.py

* revert space

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add additional links/resources to stale.yml message (#3467)

* Update stale.yml

* cleanup

* Update stale.yml

* reformat

* Update stale.yml HUB URL (#3468)

* Stale `github.actor` bug fix (#3483)

* Explicit `model.eval()` call `if opt.train=False` (#3475)

* call model.eval() when opt.train is False

call model.eval() when opt.train is False

* single-line if statement

* cleanup

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* check_requirements() exclude `opencv-python` (#3495)

Fix for 3rd party or contrib versions of installed OpenCV as in https://github.com/ultralytics/yolov5/issues/3494.

* Earlier `assert` for cpu and half option (#3508)

* early assert for cpu and half option

early assert for cpu and half option

* Modified comment

Modified comment

* Update tutorial.ipynb (#3510)

* Reduce test.py results spacing (#3511)

* Update README.md (#3512)

* Update README.md

Minor modifications

* 850 width

* Update greetings.yml

revert greeting change as PRs will now merge to master.

Co-authored-by: Piotr Skalski <SkalskiP@users.noreply.github.com>
Co-authored-by: SkalskiP <piotr.skalski92@gmail.com>
Co-authored-by: Peretz Cohen <pizzaz93@users.noreply.github.com>
Co-authored-by: tudoulei <34886368+tudoulei@users.noreply.github.com>
Co-authored-by: chocosaj <chocosaj@users.noreply.github.com>
Co-authored-by: BuildTools <unconfigured@null.spigotmc.org>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: Sam_S <SamSamhuns@users.noreply.github.com>
Co-authored-by: Samridha Shrestha <samridha.shrestha@g42.ai>
Co-authored-by: edificewang <609552430@qq.com>
This commit is contained in:
16 files changed
+186 -122

No files matched your search

+3 -3
View File
@@ -535,7 +535,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
# MixUp https://arxiv.org/pdf/1710.09412.pdf
if random.random() < hyp['mixup']:
img2, labels2 = load_mosaic(self, random.randint(0, self.n - 1))
r = np.random.beta(8.0, 8.0) # mixup ratio, alpha=beta=8.0
r = np.random.beta(32.0, 32.0) # mixup ratio, alpha=beta=32.0
img = (img * r + img2 * (1 - r)).astype(np.uint8)
labels = np.concatenate((labels, labels2), 0)
@@ -655,12 +655,12 @@ def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5):
hue, sat, val = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV))
dtype = img.dtype # uint8
x = np.arange(0, 256, dtype=np.int16)
x = np.arange(0, 256, dtype=r.dtype)
lut_hue = ((x * r[0]) % 180).astype(dtype)
lut_sat = np.clip(x * r[1], 0, 255).astype(dtype)
lut_val = np.clip(x * r[2], 0, 255).astype(dtype)
img_hsv = cv2.merge((cv2.LUT(hue, lut_hue), cv2.LUT(sat, lut_sat), cv2.LUT(val, lut_val))).astype(dtype)
img_hsv = cv2.merge((cv2.LUT(hue, lut_hue), cv2.LUT(sat, lut_sat), cv2.LUT(val, lut_val)))
cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) # no return needed
+42 -12
View File
@@ -1,5 +1,6 @@
# YOLOv5 general utils
import contextlib
import glob
import logging
import math
@@ -7,11 +8,13 @@ import os
import platform
import random
import re
import subprocess
import signal
import time
import urllib
from itertools import repeat
from multiprocessing.pool import ThreadPool
from pathlib import Path
from subprocess import check_output
import cv2
import numpy as np
@@ -33,6 +36,26 @@ cv2.setNumThreads(0) # prevent OpenCV from multithreading (incompatible with Py
os.environ['NUMEXPR_MAX_THREADS'] = str(min(os.cpu_count(), 8)) # NumExpr max threads
class timeout(contextlib.ContextDecorator):
# Usage: @timeout(seconds) decorator or 'with timeout(seconds):' context manager
def __init__(self, seconds, *, timeout_msg='', suppress_timeout_errors=True):
self.seconds = int(seconds)
self.timeout_message = timeout_msg
self.suppress = bool(suppress_timeout_errors)
def _timeout_handler(self, signum, frame):
raise TimeoutError(self.timeout_message)
def __enter__(self):
signal.signal(signal.SIGALRM, self._timeout_handler) # Set handler for SIGALRM
signal.alarm(self.seconds) # start countdown for SIGALRM to be raised
def __exit__(self, exc_type, exc_val, exc_tb):
signal.alarm(0) # Cancel SIGALRM if it's scheduled
if self.suppress and exc_type is TimeoutError: # Suppress TimeoutError
return True
def set_logging(rank=-1, verbose=True):
logging.basicConfig(
format="%(message)s",
@@ -53,12 +76,12 @@ def get_latest_run(search_dir='.'):
def is_docker():
# Is environment a Docker container
# Is environment a Docker container?
return Path('/workspace').exists() # or Path('/.dockerenv').exists()
def is_colab():
# Is environment a Google Colab instance
# Is environment a Google Colab instance?
try:
import google.colab
return True
@@ -66,6 +89,11 @@ def is_colab():
return False
def is_pip():
# Is file in a pip package?
return 'site-packages' in Path(__file__).absolute().parts
def emojis(str=''):
# Return platform-dependent emoji-safe version of string
return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str
@@ -80,13 +108,13 @@ def check_online():
# Check internet connectivity
import socket
try:
socket.create_connection(("1.1.1.1", 443), 5) # check host accesability
socket.create_connection(("1.1.1.1", 443), 5) # check host accessibility
return True
except OSError:
return False
def check_git_status():
def check_git_status(err_msg=', for updates see https://github.com/ultralytics/yolov5'):
# Recommend 'git pull' if code is out of date
print(colorstr('github: '), end='')
try:
@@ -95,9 +123,9 @@ def check_git_status():
assert check_online(), 'skipping check (offline)'
cmd = 'git fetch && git config --get remote.origin.url'
url = subprocess.check_output(cmd, shell=True).decode().strip().rstrip('.git') # github repo url
branch = subprocess.check_output('git rev-parse --abbrev-ref HEAD', shell=True).decode().strip() # checked out
n = int(subprocess.check_output(f'git rev-list {branch}..origin/master --count', shell=True)) # commits behind
url = check_output(cmd, shell=True, timeout=5).decode().strip().rstrip('.git') # git fetch
branch = check_output('git rev-parse --abbrev-ref HEAD', shell=True).decode().strip() # checked out
n = int(check_output(f'git rev-list {branch}..origin/master --count', shell=True)) # commits behind
if n > 0:
s = f"⚠️ WARNING: code is out of date by {n} commit{'s' * (n > 1)}. " \
f"Use 'git pull' to update or 'git clone {url}' to download latest."
@@ -105,7 +133,7 @@ def check_git_status():
s = f'up to date with {url} ✅'
print(emojis(s)) # emoji-safe
except Exception as e:
print(e)
print(f'{e}{err_msg}')
def check_python(minimum='3.7.0', required=True):
@@ -135,10 +163,11 @@ def check_requirements(requirements='requirements.txt', exclude=()):
try:
pkg.require(r)
except Exception as e: # DistributionNotFound or VersionConflict if requirements not met
n += 1
print(f"{prefix} {r} not found and is required by YOLOv5, attempting auto-update...")
try:
print(subprocess.check_output(f"pip install '{r}'", shell=True).decode())
assert check_online(), f"'pip install {r}' skipped (offline)"
print(check_output(f"pip install '{r}'", shell=True).decode())
n += 1
except Exception as e:
print(f'{prefix} {e}')
@@ -178,7 +207,8 @@ def check_file(file):
if Path(file).is_file() or file == '': # exists
return file
elif file.startswith(('http://', 'https://')): # download
url, file = file, Path(file).name
url, file = file, Path(urllib.parse.unquote(str(file))).name # url, file (decode '%2F' to '/' etc.)
file = file.split('?')[0] # parse authentication https://url.com/file.txt?auth...
print(f'Downloading {url} to {file}...')
torch.hub.download_url_to_file(url, file)
assert Path(file).exists() and Path(file).stat().st_size > 0, f'File download failed: {url}' # check
+37 -21
View File
@@ -4,6 +4,7 @@ import os
import platform
import subprocess
import time
import urllib
from pathlib import Path
import requests
@@ -16,11 +17,39 @@ def gsutil_getsize(url=''):
return eval(s.split(' ')[0]) if len(s) else 0 # bytes
def attempt_download(file, repo='ultralytics/yolov5'):
def safe_download(file, url, url2=None, min_bytes=1E0, error_msg=''):
# Attempts to download file from url or url2, checks and removes incomplete downloads < min_bytes
file = Path(file)
assert_msg = f"Downloaded file '{file}' does not exist or size is < min_bytes={min_bytes}"
try: # url1
print(f'Downloading {url} to {file}...')
torch.hub.download_url_to_file(url, str(file))
assert file.exists() and file.stat().st_size > min_bytes, assert_msg # check
except Exception as e: # url2
file.unlink(missing_ok=True) # remove partial downloads
print(f'ERROR: {e}\nRe-attempting {url2 or url} to {file}...')
os.system(f"curl -L '{url2 or url}' -o '{file}' --retry 3 -C -") # curl download, retry and resume on fail
finally:
if not file.exists() or file.stat().st_size < min_bytes: # check
file.unlink(missing_ok=True) # remove partial downloads
print(f"ERROR: {assert_msg}\n{error_msg}")
print('')
def attempt_download(file, repo='ultralytics/yolov5'): # from utils.google_utils import *; attempt_download()
# Attempt file download if does not exist
file = Path(str(file).strip().replace("'", ''))
if not file.exists():
# URL specified
name = Path(urllib.parse.unquote(str(file))).name # decode '%2F' to '/' etc.
if str(file).startswith(('http:/', 'https:/')): # download
url = str(file).replace(':/', '://') # Pathlib turns :// -> :/
name = name.split('?')[0] # parse authentication https://url.com/file.txt?auth...
safe_download(file=name, url=url, min_bytes=1E5)
return name
# GitHub assets
file.parent.mkdir(parents=True, exist_ok=True) # make parent dir (if required)
try:
response = requests.get(f'https://api.github.com/repos/{repo}/releases/latest').json() # github api
@@ -34,27 +63,14 @@ def attempt_download(file, repo='ultralytics/yolov5'):
except:
tag = 'v5.0' # current release
name = file.name
if name in assets:
msg = f'{file} missing, try downloading from https://github.com/{repo}/releases/'
redundant = False # second download option
try: # GitHub
url = f'https://github.com/{repo}/releases/download/{tag}/{name}'
print(f'Downloading {url} to {file}...')
torch.hub.download_url_to_file(url, file)
assert file.exists() and file.stat().st_size > 1E6 # check
except Exception as e: # GCP
print(f'Download error: {e}')
assert redundant, 'No secondary mirror'
url = f'https://storage.googleapis.com/{repo}/ckpt/{name}'
print(f'Downloading {url} to {file}...')
os.system(f"curl -L '{url}' -o '{file}' --retry 3 -C -") # curl download, retry and resume on fail
finally:
if not file.exists() or file.stat().st_size < 1E6: # check
file.unlink(missing_ok=True) # remove partial downloads
print(f'ERROR: Download failure: {msg}')
print('')
return
safe_download(file,
url=f'https://github.com/{repo}/releases/download/{tag}/{name}',
# url2=f'https://storage.googleapis.com/{repo}/ckpt/{name}', # backup url (optional)
min_bytes=1E5,
error_msg=f'{file} missing, try downloading from https://github.com/{repo}/releases/')
return str(file)
def gdrive_download(id='16TiPfZj7htmTyhntwcZyEEAejOUxuT6m', file='tmp.zip'):
+6 -6
View File
@@ -18,7 +18,7 @@ import torch.nn.functional as F
import torchvision
try:
import thop # for FLOPS computation
import thop # for FLOPs computation
except ImportError:
thop = None
logger = logging.getLogger(__name__)
@@ -105,13 +105,13 @@ def profile(x, ops, n=100, device=None):
x = x.to(device)
x.requires_grad = True
print(torch.__version__, device.type, torch.cuda.get_device_properties(0) if device.type == 'cuda' else '')
print(f"\n{'Params':>12s}{'GFLOPS':>12s}{'forward (ms)':>16s}{'backward (ms)':>16s}{'input':>24s}{'output':>24s}")
print(f"\n{'Params':>12s}{'GFLOPs':>12s}{'forward (ms)':>16s}{'backward (ms)':>16s}{'input':>24s}{'output':>24s}")
for m in ops if isinstance(ops, list) else [ops]:
m = m.to(device) if hasattr(m, 'to') else m # device
m = m.half() if hasattr(m, 'half') and isinstance(x, torch.Tensor) and x.dtype is torch.float16 else m # type
dtf, dtb, t = 0., 0., [0., 0., 0.] # dt forward, backward
try:
flops = thop.profile(m, inputs=(x,), verbose=False)[0] / 1E9 * 2 # GFLOPS
flops = thop.profile(m, inputs=(x,), verbose=False)[0] / 1E9 * 2 # GFLOPs
except:
flops = 0
@@ -219,13 +219,13 @@ def model_info(model, verbose=False, img_size=640):
print('%5g %40s %9s %12g %20s %10.3g %10.3g' %
(i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std()))
try: # FLOPS
try: # FLOPs
from thop import profile
stride = max(int(model.stride.max()), 32) if hasattr(model, 'stride') else 32
img = torch.zeros((1, model.yaml.get('ch', 3), stride, stride), device=next(model.parameters()).device) # input
flops = profile(deepcopy(model), inputs=(img,), verbose=False)[0] / 1E9 * 2 # stride GFLOPS
flops = profile(deepcopy(model), inputs=(img,), verbose=False)[0] / 1E9 * 2 # stride GFLOPs
img_size = img_size if isinstance(img_size, list) else [img_size, img_size] # expand if int/float
fs = ', %.1f GFLOPS' % (flops * img_size[0] / stride * img_size[1] / stride) # 640x640 GFLOPS
fs = ', %.1f GFLOPs' % (flops * img_size[0] / stride * img_size[1] / stride) # 640x640 GFLOPs
except (ImportError, Exception):
fs = ''