Python refactorings and simplifications (#7549)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Hassaan Farooq <103611273+hassaanfarooq01@users.noreply.github.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/utils/benchmarks.py

@@ -26,7 +26,6 @@ ncnn                    | `ncnn`                    | yolov8n_ncnn_model/
 
 import glob
 import platform
-import sys
 import time
 from pathlib import Path
 

ultralytics/utils/callbacks/base.py

@@ -4,6 +4,7 @@
 from collections import defaultdict
 from copy import deepcopy
 
+
 # Trainer callbacks ----------------------------------------------------------------------------------------------------
 
 

ultralytics/utils/callbacks/neptune.py

@@ -96,9 +96,7 @@ def on_train_end(trainer):
         for f in files:
             _log_plot(title=f.stem, plot_path=f)
         # Log the final model
-        run[f"weights/{trainer.args.name or trainer.args.task}/{str(trainer.best.name)}"].upload(
-            File(str(trainer.best))
-        )
+        run[f"weights/{trainer.args.name or trainer.args.task}/{trainer.best.name}"].upload(File(str(trainer.best)))
 
 
 callbacks = (

ultralytics/utils/checks.py

@@ -214,9 +214,9 @@ def check_version(
         try:
             name = current  # assigned package name to 'name' arg
             current = metadata.version(current)  # get version string from package name
-        except metadata.PackageNotFoundError:
+        except metadata.PackageNotFoundError as e:
             if hard:
-                raise ModuleNotFoundError(emojis(f"WARNING ⚠️ {current} package is required but not installed"))
+                raise ModuleNotFoundError(emojis(f"WARNING ⚠️ {current} package is required but not installed")) from e
             else:
                 return False
 

ultralytics/utils/loss.py

@@ -7,7 +7,6 @@ import torch.nn.functional as F
 from ultralytics.utils.metrics import OKS_SIGMA
 from ultralytics.utils.ops import crop_mask, xywh2xyxy, xyxy2xywh
 from ultralytics.utils.tal import RotatedTaskAlignedAssigner, TaskAlignedAssigner, dist2bbox, dist2rbox, make_anchors
-
 from .metrics import bbox_iou, probiou
 from .tal import bbox2dist
 

ultralytics/utils/ops.py

@@ -40,7 +40,7 @@ class Profile(contextlib.ContextDecorator):
         """
         self.t = t
         self.device = device
-        self.cuda = True if (device and str(device)[:4] == "cuda") else False
+        self.cuda = bool(device and str(device).startswith("cuda"))
 
     def __enter__(self):
         """Start timing."""
@@ -534,12 +534,11 @@ def xyxyxyxy2xywhr(corners):
         # especially some objects are cut off by augmentations in dataloader.
         (x, y), (w, h), angle = cv2.minAreaRect(pts)
         rboxes.append([x, y, w, h, angle / 180 * np.pi])
-    rboxes = (
+    return (
         torch.tensor(rboxes, device=corners.device, dtype=corners.dtype)
         if is_torch
         else np.asarray(rboxes, dtype=points.dtype)
-    )
-    return rboxes
+    )  # rboxes
 
 
 def xywhr2xyxyxyxy(center):

ultralytics/utils/plotting.py

@@ -13,7 +13,6 @@ from PIL import Image, ImageDraw, ImageFont
 from PIL import __version__ as pil_version
 
 from ultralytics.utils import LOGGER, TryExcept, ops, plt_settings, threaded
-
 from .checks import check_font, check_version, is_ascii
 from .files import increment_path
 
@@ -433,7 +432,7 @@ class Annotator:
             center_kpt (int): centroid pose index for workout monitoring
             line_thickness (int): thickness for text display
         """
-        angle_text, count_text, stage_text = (f" {angle_text:.2f}", "Steps : " + f"{count_text}", f" {stage_text}")
+        angle_text, count_text, stage_text = (f" {angle_text:.2f}", f"Steps : {count_text}", f" {stage_text}")
         font_scale = 0.6 + (line_thickness / 10.0)
 
         # Draw angle
@@ -773,12 +772,11 @@ def plot_images(
                                 im[y : y + h, x : x + w, :][mask] * 0.4 + np.array(color) * 0.6
                             )
                 annotator.fromarray(im)
-    if save:
-        annotator.im.save(fname)  # save
-        if on_plot:
-            on_plot(fname)
-    else:
+    if not save:
         return np.asarray(annotator.im)
+    annotator.im.save(fname)  # save
+    if on_plot:
+        on_plot(fname)
 
 
 @plt_settings()

ultralytics/utils/tal.py

@@ -288,8 +288,7 @@ class RotatedTaskAlignedAssigner(TaskAlignedAssigner):
         norm_ad = (ad * ad).sum(dim=-1)
         ap_dot_ab = (ap * ab).sum(dim=-1)
         ap_dot_ad = (ap * ad).sum(dim=-1)
-        is_in_box = (ap_dot_ab >= 0) & (ap_dot_ab <= norm_ab) & (ap_dot_ad >= 0) & (ap_dot_ad <= norm_ad)
-        return is_in_box
+        return (ap_dot_ab >= 0) & (ap_dot_ab <= norm_ab) & (ap_dot_ad >= 0) & (ap_dot_ad <= norm_ad)  # is_in_box
 
 
 def make_anchors(feats, strides, grid_cell_offset=0.5):