ultralytics 8.0.163 add new gpu-latest runner to CI actions (#4565)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Maia Numerosky <17316848+maianumerosky@users.noreply.github.com>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.162'
+__version__ = '8.0.163'
 
 from ultralytics.models import RTDETR, SAM, YOLO
 from ultralytics.models.fastsam import FastSAM

ultralytics/cfg/__init__.py

@@ -4,7 +4,6 @@ import contextlib
 import re
 import shutil
 import sys
-from difflib import get_close_matches
 from pathlib import Path
 from types import SimpleNamespace
 from typing import Dict, List, Union
@@ -177,6 +176,8 @@ def check_dict_alignment(base: Dict, custom: Dict, e=None):
     base_keys, custom_keys = (set(x.keys()) for x in (base, custom))
     mismatched = [k for k in custom_keys if k not in base_keys]
     if mismatched:
+        from difflib import get_close_matches
+
         string = ''
         for x in mismatched:
             matches = get_close_matches(x, base_keys)  # key list
@@ -373,11 +374,7 @@ def entrypoint(debug=''):
         mode = DEFAULT_CFG.mode or 'predict'
         LOGGER.warning(f"WARNING ⚠️ 'mode' is missing. Valid modes are {MODES}. Using default 'mode={mode}'.")
     elif mode not in MODES:
-        if mode not in ('checks', checks):
-            raise ValueError(f"Invalid 'mode={mode}'. Valid modes are {MODES}.\n{CLI_HELP_MSG}")
-        LOGGER.warning("WARNING ⚠️ 'yolo mode=checks' is deprecated. Use 'yolo checks' instead.")
-        checks.check_yolo()
-        return
+        raise ValueError(f"Invalid 'mode={mode}'. Valid modes are {MODES}.\n{CLI_HELP_MSG}")
 
     # Task
     task = overrides.pop('task', None)

ultralytics/data/augment.py

@@ -483,7 +483,7 @@ class RandomHSV:
         self.vgain = vgain
 
     def __call__(self, labels):
-        """Applies random horizontal or vertical flip to an image with a given probability."""
+        """Applies image HSV augmentation"""
         img = labels['img']
         if self.hgain or self.sgain or self.vgain:
             r = np.random.uniform(-1, 1, 3) * [self.hgain, self.sgain, self.vgain] + 1  # random gains
@@ -501,6 +501,7 @@ class RandomHSV:
 
 
 class RandomFlip:
+    """Applies random horizontal or vertical flip to an image with a given probability."""
 
     def __init__(self, p=0.5, direction='horizontal', flip_idx=None) -> None:
         assert direction in ['horizontal', 'vertical'], f'Support direction `horizontal` or `vertical`, got {direction}'
@@ -643,7 +644,9 @@ class CopyPaste:
 
 
 class Albumentations:
-    """YOLOv8 Albumentations class (optional, only used if package is installed)"""
+    """Albumentations transformations. Optional, uninstall package to disable.
+    Applies Blur, Median Blur, convert to grayscale, Contrast Limited Adaptive Histogram Equalization,
+    random change of brightness and contrast, RandomGamma and lowering of image quality by compression."""
 
     def __init__(self, p=1.0):
         """Initialize the transform object for YOLO bbox formatted params."""

ultralytics/engine/exporter.py

@@ -159,7 +159,10 @@ class Exporter:
             raise ValueError(f"Invalid export format='{format}'. Valid formats are {fmts}")
         jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle, ncnn = flags  # export booleans
 
-        # Load PyTorch model
+        # Device
+        if format == 'engine' and self.args.device is None:
+            LOGGER.warning('WARNING ⚠️ TensorRT requires GPU export, automatically assigning device=0')
+            self.args.device = '0'
         self.device = select_device('cpu' if self.args.device is None else self.args.device)
 
         # Checks

ultralytics/utils/benchmarks.py

@@ -182,6 +182,7 @@ class ProfileModels:
                  num_warmup_runs=10,
                  min_time=60,
                  imgsz=640,
+                 half=True,
                  trt=True,
                  device=None):
         self.paths = paths
@@ -189,6 +190,7 @@ class ProfileModels:
         self.num_warmup_runs = num_warmup_runs
         self.min_time = min_time
         self.imgsz = imgsz
+        self.half = half
         self.trt = trt  # run TensorRT profiling
         self.device = device or torch.device(0 if torch.cuda.is_available() else 'cpu')
 
@@ -209,12 +211,12 @@ class ProfileModels:
                 model_info = model.info()
                 if self.trt and self.device.type != 'cpu' and not engine_file.is_file():
                     engine_file = model.export(format='engine',
-                                               half=True,
+                                               half=self.half,
                                                imgsz=self.imgsz,
                                                device=self.device,
                                                verbose=False)
                 onnx_file = model.export(format='onnx',
-                                         half=True,
+                                         half=self.half,
                                          imgsz=self.imgsz,
                                          simplify=True,
                                          device=self.device,

ultralytics/utils/checks.py

@@ -507,3 +507,28 @@ def print_args(args: Optional[dict] = None, show_file=True, show_func=False):
         file = Path(file).stem
     s = (f'{file}: ' if show_file else '') + (f'{func}: ' if show_func else '')
     LOGGER.info(colorstr(s) + ', '.join(f'{k}={strip_auth(v)}' for k, v in args.items()))
+
+
+def cuda_device_count() -> int:
+    """Get the number of NVIDIA GPUs available in the environment.
+
+    Returns:
+        (int): The number of NVIDIA GPUs available.
+    """
+    try:
+        # Run the nvidia-smi command and capture its output
+        output = subprocess.check_output(['nvidia-smi', '--query-gpu=count', '--format=csv,noheader,nounits'],
+                                         encoding='utf-8')
+        return int(output.strip())
+    except (subprocess.CalledProcessError, FileNotFoundError):
+        # If the command fails or nvidia-smi is not found, assume no GPUs are available
+        return 0
+
+
+def cuda_is_available() -> bool:
+    """Check if CUDA is available in the environment.
+
+    Returns:
+        (bool): True if one or more NVIDIA GPUs are available, False otherwise.
+    """
+    return cuda_device_count() > 0