`ultralytics 8.2.28` improved NMS speeds (#13315)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/13341/head v8.2.28
Glenn Jocher 6 months ago committed by GitHub
parent 90f2a4226c
commit 5df2d167a9
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  1. 2
      ultralytics/__init__.py
  2. 2
      ultralytics/nn/autobackend.py
  3. 12
      ultralytics/utils/ops.py

@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.27"
__version__ = "8.2.28"
import os

@ -184,7 +184,7 @@ class AutoBackend(nn.Module):
LOGGER.info(f"Loading {w} for ONNX Runtime inference...")
check_requirements(("onnx", "onnxruntime-gpu" if cuda else "onnxruntime"))
if IS_RASPBERRYPI or IS_JETSON:
# Fix error: module 'numpy.linalg._umath_linalg' has no attribute '_ilp64' when exporting to Tensorflow SavedModel on RPi and Jetson
# Fix 'numpy.linalg._umath_linalg' has no attribute '_ilp64' for TF SavedModel on RPi and Jetson
check_requirements("numpy==1.23.5")
import onnxruntime

@ -402,7 +402,7 @@ def xyxy2xywh(x):
def xywh2xyxy(x):
"""
Convert bounding box coordinates from (x, y, width, height) format to (x1, y1, x2, y2) format where (x1, y1) is the
top-left corner and (x2, y2) is the bottom-right corner.
top-left corner and (x2, y2) is the bottom-right corner. Note: ops per 2 channels faster than per channel.
Args:
x (np.ndarray | torch.Tensor): The input bounding box coordinates in (x, y, width, height) format.
@ -412,12 +412,10 @@ def xywh2xyxy(x):
"""
assert x.shape[-1] == 4, f"input shape last dimension expected 4 but input shape is {x.shape}"
y = torch.empty_like(x) if isinstance(x, torch.Tensor) else np.empty_like(x) # faster than clone/copy
dw = x[..., 2] / 2 # half-width
dh = x[..., 3] / 2 # half-height
y[..., 0] = x[..., 0] - dw # top left x
y[..., 1] = x[..., 1] - dh # top left y
y[..., 2] = x[..., 0] + dw # bottom right x
y[..., 3] = x[..., 1] + dh # bottom right y
xy = x[..., :2] # centers
wh = x[..., 2:] / 2 # half width-height
y[..., :2] = xy - wh # top left xy
y[..., 2:] = xy + wh # bottom right xy
return y

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