`ultralytics 8.3.8` replace `contextlib` with `try` for speed (#16782)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.3.7"
+__version__ = "8.3.8"
 
 import os
 

ultralytics/cfg/__init__.py

@@ -669,9 +669,10 @@ def smart_value(v):
     elif v_lower == "false":
         return False
     else:
-        with contextlib.suppress(Exception):
+        try:
             return eval(v)
-        return v
+        except:  # noqa E722
+            return v
 
 
 def entrypoint(debug=""):

ultralytics/data/dataset.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import json
 from collections import defaultdict
 from itertools import repeat
@@ -483,7 +482,7 @@ class ClassificationDataset:
         desc = f"{self.prefix}Scanning {self.root}..."
         path = Path(self.root).with_suffix(".cache")  # *.cache file path
 
-        with contextlib.suppress(FileNotFoundError, AssertionError, AttributeError):
+        try:
             cache = load_dataset_cache_file(path)  # attempt to load a *.cache file
             assert cache["version"] == DATASET_CACHE_VERSION  # matches current version
             assert cache["hash"] == get_hash([x[0] for x in self.samples])  # identical hash
@@ -495,24 +494,25 @@ class ClassificationDataset:
                     LOGGER.info("\n".join(cache["msgs"]))  # display warnings
             return samples
 
-        # Run scan if *.cache retrieval failed
-        nf, nc, msgs, samples, x = 0, 0, [], [], {}
-        with ThreadPool(NUM_THREADS) as pool:
-            results = pool.imap(func=verify_image, iterable=zip(self.samples, repeat(self.prefix)))
-            pbar = TQDM(results, desc=desc, total=len(self.samples))
-            for sample, nf_f, nc_f, msg in pbar:
-                if nf_f:
-                    samples.append(sample)
-                if msg:
-                    msgs.append(msg)
-                nf += nf_f
-                nc += nc_f
-                pbar.desc = f"{desc} {nf} images, {nc} corrupt"
-            pbar.close()
-        if msgs:
-            LOGGER.info("\n".join(msgs))
-        x["hash"] = get_hash([x[0] for x in self.samples])
-        x["results"] = nf, nc, len(samples), samples
-        x["msgs"] = msgs  # warnings
-        save_dataset_cache_file(self.prefix, path, x, DATASET_CACHE_VERSION)
-        return samples
+        except (FileNotFoundError, AssertionError, AttributeError):
+            # Run scan if *.cache retrieval failed
+            nf, nc, msgs, samples, x = 0, 0, [], [], {}
+            with ThreadPool(NUM_THREADS) as pool:
+                results = pool.imap(func=verify_image, iterable=zip(self.samples, repeat(self.prefix)))
+                pbar = TQDM(results, desc=desc, total=len(self.samples))
+                for sample, nf_f, nc_f, msg in pbar:
+                    if nf_f:
+                        samples.append(sample)
+                    if msg:
+                        msgs.append(msg)
+                    nf += nf_f
+                    nc += nc_f
+                    pbar.desc = f"{desc} {nf} images, {nc} corrupt"
+                pbar.close()
+            if msgs:
+                LOGGER.info("\n".join(msgs))
+            x["hash"] = get_hash([x[0] for x in self.samples])
+            x["results"] = nf, nc, len(samples), samples
+            x["msgs"] = msgs  # warnings
+            save_dataset_cache_file(self.prefix, path, x, DATASET_CACHE_VERSION)
+            return samples

ultralytics/data/utils.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import hashlib
 import json
 import os
@@ -60,12 +59,14 @@ def exif_size(img: Image.Image):
     """Returns exif-corrected PIL size."""
     s = img.size  # (width, height)
     if img.format == "JPEG":  # only support JPEG images
-        with contextlib.suppress(Exception):
+        try:
             exif = img.getexif()
             if exif:
                 rotation = exif.get(274, None)  # the EXIF key for the orientation tag is 274
                 if rotation in {6, 8}:  # rotation 270 or 90
                     s = s[1], s[0]
+        except:  # noqa E722
+            pass
     return s
 
 

ultralytics/nn/autobackend.py

@@ -1,7 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
 import ast
-import contextlib
 import json
 import platform
 import zipfile
@@ -45,8 +44,10 @@ def check_class_names(names):
 def default_class_names(data=None):
     """Applies default class names to an input YAML file or returns numerical class names."""
     if data:
-        with contextlib.suppress(Exception):
+        try:
             return yaml_load(check_yaml(data))["names"]
+        except:  # noqa E722
+            pass
     return {i: f"class{i}" for i in range(999)}  # return default if above errors
 
 
@@ -321,8 +322,10 @@ class AutoBackend(nn.Module):
             with open(w, "rb") as f:
                 gd.ParseFromString(f.read())
             frozen_func = wrap_frozen_graph(gd, inputs="x:0", outputs=gd_outputs(gd))
-            with contextlib.suppress(StopIteration):  # find metadata in SavedModel alongside GraphDef
+            try:  # find metadata in SavedModel alongside GraphDef
                 metadata = next(Path(w).resolve().parent.rglob(f"{Path(w).stem}_saved_model*/metadata.yaml"))
+            except StopIteration:
+                pass
 
         # TFLite or TFLite Edge TPU
         elif tflite or edgetpu:  # https://www.tensorflow.org/lite/guide/python#install_tensorflow_lite_for_python
@@ -345,10 +348,12 @@ class AutoBackend(nn.Module):
             input_details = interpreter.get_input_details()  # inputs
             output_details = interpreter.get_output_details()  # outputs
             # Load metadata
-            with contextlib.suppress(zipfile.BadZipFile):
+            try:
                 with zipfile.ZipFile(w, "r") as model:
                     meta_file = model.namelist()[0]
                     metadata = ast.literal_eval(model.read(meta_file).decode("utf-8"))
+            except zipfile.BadZipFile:
+                pass
 
         # TF.js
         elif tfjs:

ultralytics/nn/tasks.py

@@ -2,6 +2,7 @@
 
 import contextlib
 import pickle
+import re
 import types
 from copy import deepcopy
 from pathlib import Path
@@ -958,8 +959,10 @@ def parse_model(d, ch, verbose=True):  # model_dict, input_channels(3)
         m = getattr(torch.nn, m[3:]) if "nn." in m else globals()[m]  # get module
         for j, a in enumerate(args):
             if isinstance(a, str):
-                with contextlib.suppress(ValueError):
+                try:
                     args[j] = locals()[a] if a in locals() else ast.literal_eval(a)
+                except ValueError:
+                    pass
 
         n = n_ = max(round(n * depth), 1) if n > 1 else n  # depth gain
         if m in {
@@ -1072,8 +1075,6 @@ def parse_model(d, ch, verbose=True):  # model_dict, input_channels(3)
 
 def yaml_model_load(path):
     """Load a YOLOv8 model from a YAML file."""
-    import re
-
     path = Path(path)
     if path.stem in (f"yolov{d}{x}6" for x in "nsmlx" for d in (5, 8)):
         new_stem = re.sub(r"(\d+)([nslmx])6(.+)?$", r"\1\2-p6\3", path.stem)
@@ -1100,11 +1101,10 @@ def guess_model_scale(model_path):
     Returns:
         (str): The size character of the model's scale, which can be n, s, m, l, or x.
     """
-    with contextlib.suppress(AttributeError):
-        import re
-
+    try:
         return re.search(r"yolo[v]?\d+([nslmx])", Path(model_path).stem).group(1)  # n, s, m, l, or x
-    return ""
+    except AttributeError:
+        return ""
 
 
 def guess_model_task(model):
@@ -1137,17 +1137,23 @@ def guess_model_task(model):
 
     # Guess from model cfg
     if isinstance(model, dict):
-        with contextlib.suppress(Exception):
+        try:
             return cfg2task(model)
+        except:  # noqa E722
+            pass
 
     # Guess from PyTorch model
     if isinstance(model, nn.Module):  # PyTorch model
         for x in "model.args", "model.model.args", "model.model.model.args":
-            with contextlib.suppress(Exception):
+            try:
                 return eval(x)["task"]
+            except:  # noqa E722
+                pass
         for x in "model.yaml", "model.model.yaml", "model.model.model.yaml":
-            with contextlib.suppress(Exception):
+            try:
                 return cfg2task(eval(x))
+            except:  # noqa E722
+                pass
 
         for m in model.modules():
             if isinstance(m, Segment):

ultralytics/utils/__init__.py

@@ -523,10 +523,11 @@ def read_device_model() -> str:
     Returns:
         (str): Model file contents if read successfully or empty string otherwise.
     """
-    with contextlib.suppress(Exception):
+    try:
         with open("/proc/device-tree/model") as f:
             return f.read()
-    return ""
+    except:  # noqa E722
+        return ""
 
 
 def is_ubuntu() -> bool:
@@ -536,10 +537,11 @@ def is_ubuntu() -> bool:
     Returns:
         (bool): True if OS is Ubuntu, False otherwise.
     """
-    with contextlib.suppress(FileNotFoundError):
+    try:
         with open("/etc/os-release") as f:
             return "ID=ubuntu" in f.read()
-    return False
+    except FileNotFoundError:
+        return False
 
 
 def is_colab():
@@ -569,11 +571,7 @@ def is_jupyter():
     Returns:
         (bool): True if running inside a Jupyter Notebook, False otherwise.
     """
-    with contextlib.suppress(Exception):
-        from IPython import get_ipython
-
-        return get_ipython() is not None
-    return False
+    return "get_ipython" in locals()
 
 
 def is_docker() -> bool:
@@ -583,10 +581,11 @@ def is_docker() -> bool:
     Returns:
         (bool): True if the script is running inside a Docker container, False otherwise.
     """
-    with contextlib.suppress(Exception):
+    try:
         with open("/proc/self/cgroup") as f:
             return "docker" in f.read()
-    return False
+    except:  # noqa E722
+        return False
 
 
 def is_raspberrypi() -> bool:
@@ -617,14 +616,15 @@ def is_online() -> bool:
     Returns:
         (bool): True if connection is successful, False otherwise.
     """
-    with contextlib.suppress(Exception):
+    try:
         assert str(os.getenv("YOLO_OFFLINE", "")).lower() != "true"  # check if ENV var YOLO_OFFLINE="True"
         import socket
 
         for dns in ("1.1.1.1", "8.8.8.8"):  # check Cloudflare and Google DNS
             socket.create_connection(address=(dns, 80), timeout=2.0).close()
             return True
-    return False
+    except:  # noqa E722
+        return False
 
 
 def is_pip_package(filepath: str = __name__) -> bool:
@@ -711,9 +711,11 @@ def get_git_origin_url():
         (str | None): The origin URL of the git repository or None if not git directory.
     """
     if IS_GIT_DIR:
-        with contextlib.suppress(subprocess.CalledProcessError):
+        try:
             origin = subprocess.check_output(["git", "config", "--get", "remote.origin.url"])
             return origin.decode().strip()
+        except subprocess.CalledProcessError:
+            return None
 
 
 def get_git_branch():
@@ -724,9 +726,11 @@ def get_git_branch():
         (str | None): The current git branch name or None if not a git directory.
     """
     if IS_GIT_DIR:
-        with contextlib.suppress(subprocess.CalledProcessError):
+        try:
             origin = subprocess.check_output(["git", "rev-parse", "--abbrev-ref", "HEAD"])
             return origin.decode().strip()
+        except subprocess.CalledProcessError:
+            return None
 
 
 def get_default_args(func):
@@ -751,9 +755,11 @@ def get_ubuntu_version():
         (str): Ubuntu version or None if not an Ubuntu OS.
     """
     if is_ubuntu():
-        with contextlib.suppress(FileNotFoundError, AttributeError):
+        try:
             with open("/etc/os-release") as f:
                 return re.search(r'VERSION_ID="(\d+\.\d+)"', f.read())[1]
+        except (FileNotFoundError, AttributeError):
+            return None
 
 
 def get_user_config_dir(sub_dir="Ultralytics"):

ultralytics/utils/callbacks/tensorboard.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 
 from ultralytics.utils import LOGGER, SETTINGS, TESTS_RUNNING, colorstr
 
@@ -45,26 +44,27 @@ def _log_tensorboard_graph(trainer):
         warnings.simplefilter("ignore", category=torch.jit.TracerWarning)  # suppress jit trace warning
 
         # Try simple method first (YOLO)
-        with contextlib.suppress(Exception):
+        try:
             trainer.model.eval()  # place in .eval() mode to avoid BatchNorm statistics changes
             WRITER.add_graph(torch.jit.trace(de_parallel(trainer.model), im, strict=False), [])
             LOGGER.info(f"{PREFIX}model graph visualization added ✅")
             return
 
-        # Fallback to TorchScript export steps (RTDETR)
-        try:
-            model = deepcopy(de_parallel(trainer.model))
-            model.eval()
-            model = model.fuse(verbose=False)
-            for m in model.modules():
-                if hasattr(m, "export"):  # Detect, RTDETRDecoder (Segment and Pose use Detect base class)
-                    m.export = True
-                    m.format = "torchscript"
-            model(im)  # dry run
-            WRITER.add_graph(torch.jit.trace(model, im, strict=False), [])
-            LOGGER.info(f"{PREFIX}model graph visualization added ✅")
-        except Exception as e:
-            LOGGER.warning(f"{PREFIX}WARNING ⚠️ TensorBoard graph visualization failure {e}")
+        except:  # noqa E722
+            # Fallback to TorchScript export steps (RTDETR)
+            try:
+                model = deepcopy(de_parallel(trainer.model))
+                model.eval()
+                model = model.fuse(verbose=False)
+                for m in model.modules():
+                    if hasattr(m, "export"):  # Detect, RTDETRDecoder (Segment and Pose use Detect base class)
+                        m.export = True
+                        m.format = "torchscript"
+                model(im)  # dry run
+                WRITER.add_graph(torch.jit.trace(model, im, strict=False), [])
+                LOGGER.info(f"{PREFIX}model graph visualization added ✅")
+            except Exception as e:
+                LOGGER.warning(f"{PREFIX}WARNING ⚠️ TensorBoard graph visualization failure {e}")
 
 
 def on_pretrain_routine_start(trainer):

ultralytics/utils/checks.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import glob
 import inspect
 import math
@@ -271,11 +270,13 @@ def check_latest_pypi_version(package_name="ultralytics"):
     Returns:
         (str): The latest version of the package.
     """
-    with contextlib.suppress(Exception):
+    try:
         requests.packages.urllib3.disable_warnings()  # Disable the InsecureRequestWarning
         response = requests.get(f"https://pypi.org/pypi/{package_name}/json", timeout=3)
         if response.status_code == 200:
             return response.json()["info"]["version"]
+    except:  # noqa E722
+        return None
 
 
 def check_pip_update_available():
@@ -286,7 +287,7 @@ def check_pip_update_available():
         (bool): True if an update is available, False otherwise.
     """
     if ONLINE and IS_PIP_PACKAGE:
-        with contextlib.suppress(Exception):
+        try:
             from ultralytics import __version__
 
             latest = check_latest_pypi_version()
@@ -296,6 +297,8 @@ def check_pip_update_available():
                     f"Update with 'pip install -U ultralytics'"
                 )
                 return True
+        except:  # noqa E722
+            pass
     return False
 
 
@@ -577,10 +580,12 @@ def check_yolo(verbose=True, device=""):
         ram = psutil.virtual_memory().total
         total, used, free = shutil.disk_usage("/")
         s = f"({os.cpu_count()} CPUs, {ram / gib:.1f} GB RAM, {(total - free) / gib:.1f}/{total / gib:.1f} GB disk)"
-        with contextlib.suppress(Exception):  # clear display if ipython is installed
+        try:
             from IPython import display
 
-            display.clear_output()
+            display.clear_output()  # clear display if notebook
+        except ImportError:
+            pass
     else:
         s = ""
 
@@ -707,9 +712,10 @@ def check_amp(model):
 
 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."""
-    with contextlib.suppress(Exception):
+    try:
         return subprocess.check_output(f"git -C {path} describe --tags --long --always", shell=True).decode()[:-1]
-    return ""
+    except:  # noqa E722
+        return ""
 
 
 def print_args(args: Optional[dict] = None, show_file=True, show_func=False):

ultralytics/utils/downloads.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import re
 import shutil
 import subprocess
@@ -53,7 +52,7 @@ def is_url(url, check=False):
         valid = is_url("https://www.example.com")
         ```
     """
-    with contextlib.suppress(Exception):
+    try:
         url = str(url)
         result = parse.urlparse(url)
         assert all([result.scheme, result.netloc])  # check if is url
@@ -61,7 +60,8 @@ def is_url(url, check=False):
             with request.urlopen(url) as response:
                 return response.getcode() == 200  # check if exists online
         return True
-    return False
+    except:  # noqa E722
+        return False
 
 
 def delete_dsstore(path, files_to_delete=(".DS_Store", "__MACOSX")):

ultralytics/utils/plotting.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import math
 import warnings
 from pathlib import Path
@@ -1115,10 +1114,12 @@ def plot_images(
                             mask = mask.astype(bool)
                         else:
                             mask = image_masks[j].astype(bool)
-                        with contextlib.suppress(Exception):
+                        try:
                             im[y : y + h, x : x + w, :][mask] = (
                                 im[y : y + h, x : x + w, :][mask] * 0.4 + np.array(color) * 0.6
                             )
+                        except:  # noqa E722
+                            pass
                 annotator.fromarray(im)
     if not save:
         return np.asarray(annotator.im)

ultralytics/utils/torch_utils.py

@@ -1,6 +1,5 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-import contextlib
 import gc
 import math
 import os
@@ -113,13 +112,15 @@ def get_cpu_info():
     from ultralytics.utils import PERSISTENT_CACHE  # avoid circular import error
 
     if "cpu_info" not in PERSISTENT_CACHE:
-        with contextlib.suppress(Exception):
+        try:
             import cpuinfo  # pip install py-cpuinfo
 
             k = "brand_raw", "hardware_raw", "arch_string_raw"  # keys sorted by preference
             info = cpuinfo.get_cpu_info()  # info dict
             string = info.get(k[0] if k[0] in info else k[1] if k[1] in info else k[2], "unknown")
             PERSISTENT_CACHE["cpu_info"] = string.replace("(R)", "").replace("CPU ", "").replace("@ ", "")
+        except:  # noqa E722
+            pass
     return PERSISTENT_CACHE.get("cpu_info", "unknown")