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ultralytics 8.0.47 Docker and reformat updates (#1153)

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Glenn Jocher 2023-02-25 22:49:19 -08:00 • committed by GitHub
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commit a58f766f94
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41 changed files with 224 additions and 201 deletions
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25
ultralytics/yolo/utils/benchmarks.py
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@ -30,14 +30,14 @@ import pandas as pd
from ultralytics import YOLO
from ultralytics.yolo.engine.exporter import export_formats
from ultralytics.yolo.utils import LOGGER, ROOT, SETTINGS
from ultralytics.yolo.utils import LINUX, LOGGER, ROOT, SETTINGS
from ultralytics.yolo.utils.checks import check_yolo
from ultralytics.yolo.utils.downloads import download
from ultralytics.yolo.utils.files import file_size
from ultralytics.yolo.utils.torch_utils import select_device
def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt', imgsz=160, half=False, device='cpu', hard_fail=0.30):
def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt', imgsz=160, half=False, device='cpu', hard_fail=False):
device = select_device(device, verbose=False)
if isinstance(model, (str, Path)):
model = YOLO(model)
@ -45,11 +45,10 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt', imgsz=160, hal
y = []
t0 = time.time()
for i, (name, format, suffix, cpu, gpu) in export_formats().iterrows(): # index, (name, format, suffix, CPU, GPU)
emoji = '❌' # indicates export failure
try:
assert i not in (9, 10), 'inference not supported' # Edge TPU and TF.js are unsupported
assert i != 5 or platform.system() == 'Darwin', 'inference only supported on macOS>=10.13' # CoreML
assert i != 11 or model.task != 'classify', 'paddle-classify bug'
assert i != 11, 'paddle exports coming soon'
assert i != 9 or LINUX, 'Edge TPU export only supported on Linux'
if 'cpu' in device.type:
assert cpu, 'inference not supported on CPU'
if 'cuda' in device.type:
@ -61,13 +60,16 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt', imgsz=160, hal
export = model # PyTorch format
else:
filename = model.export(imgsz=imgsz, format=format, half=half, device=device) # all others
export = YOLO(filename)
export = YOLO(filename, task=model.task)
assert suffix in str(filename), 'export failed'
emoji = '❎' # indicates export succeeded
# Predict
assert i not in (9, 10), 'inference not supported' # Edge TPU and TF.js are unsupported
assert i != 5 or platform.system() == 'Darwin', 'inference only supported on macOS>=10.13' # CoreML
if not (ROOT / 'assets/bus.jpg').exists():
download(url='https://ultralytics.com/images/bus.jpg', dir=ROOT / 'assets')
export.predict(ROOT / 'assets/bus.jpg', imgsz=imgsz, device=device, half=half) # test
export.predict(ROOT / 'assets/bus.jpg', imgsz=imgsz, device=device, half=half)
# Validate
if model.task == 'detect':
@ -84,17 +86,16 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt', imgsz=160, hal
if hard_fail:
assert type(e) is AssertionError, f'Benchmark hard_fail for {name}: {e}'
LOGGER.warning(f'ERROR ❌️ Benchmark failure for {name}: {e}')
y.append([name, '❌', None, None, None]) # mAP, t_inference
y.append([name, emoji, None, None, None]) # mAP, t_inference
# Print results
check_yolo(device=device) # print system info
c = ['Format', 'Status❔', 'Size (MB)', key, 'Inference time (ms/im)']
df = pd.DataFrame(y, columns=c)
df = pd.DataFrame(y, columns=['Format', 'Status❔', 'Size (MB)', key, 'Inference time (ms/im)'])
name = Path(model.ckpt_path).name
s = f'\nBenchmarks complete for {name} on {data} at imgsz={imgsz} ({time.time() - t0:.2f}s)\n{df}\n'
LOGGER.info(s)
with open('benchmarks.log', 'a') as f:
with open('benchmarks.log', 'a', errors='ignore', encoding='utf-8') as f:
f.write(s)
if hard_fail and isinstance(hard_fail, float):