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ultralytics 8.1.43 40% faster ultralytics imports (#9547)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-04-05 15:29:09 +02:00 • committed by GitHub
parent 99c61d6f7b
commit a2628657a1
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GPG key ID: B5690EEEBB952194
21 changed files with 240 additions and 225 deletions
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16
ultralytics/utils/plotting.py
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@ -671,8 +671,8 @@ class Annotator:
@plt_settings()
def plot_labels(boxes, cls, names=(), save_dir=Path(""), on_plot=None):
"""Plot training labels including class histograms and box statistics."""
import pandas as pd
import seaborn as sn
import pandas # scope for faster 'import ultralytics'
import seaborn # scope for faster 'import ultralytics'
# Filter matplotlib>=3.7.2 warning and Seaborn use_inf and is_categorical FutureWarnings
warnings.filterwarnings("ignore", category=UserWarning, message="The figure layout has changed to tight")
@ -682,10 +682,10 @@ def plot_labels(boxes, cls, names=(), save_dir=Path(""), on_plot=None):
LOGGER.info(f"Plotting labels to {save_dir / 'labels.jpg'}... ")
nc = int(cls.max() + 1) # number of classes
boxes = boxes[:1000000] # limit to 1M boxes
x = pd.DataFrame(boxes, columns=["x", "y", "width", "height"])
x = pandas.DataFrame(boxes, columns=["x", "y", "width", "height"])
# Seaborn correlogram
sn.pairplot(x, corner=True, diag_kind="auto", kind="hist", diag_kws=dict(bins=50), plot_kws=dict(pmax=0.9))
seaborn.pairplot(x, corner=True, diag_kind="auto", kind="hist", diag_kws=dict(bins=50), plot_kws=dict(pmax=0.9))
plt.savefig(save_dir / "labels_correlogram.jpg", dpi=200)
plt.close()
@ -700,8 +700,8 @@ def plot_labels(boxes, cls, names=(), save_dir=Path(""), on_plot=None):
ax[0].set_xticklabels(list(names.values()), rotation=90, fontsize=10)
else:
ax[0].set_xlabel("classes")
sn.histplot(x, x="x", y="y", ax=ax[2], bins=50, pmax=0.9)
sn.histplot(x, x="width", y="height", ax=ax[3], bins=50, pmax=0.9)
seaborn.histplot(x, x="x", y="y", ax=ax[2], bins=50, pmax=0.9)
seaborn.histplot(x, x="width", y="height", ax=ax[3], bins=50, pmax=0.9)
# Rectangles
boxes[:, 0:2] = 0.5 # center
@ -933,7 +933,7 @@ def plot_results(file="path/to/results.csv", dir="", segment=False, pose=False,
plot_results('path/to/results.csv', segment=True)
```
"""
import pandas as pd
import pandas as pd # scope for faster 'import ultralytics'
from scipy.ndimage import gaussian_filter1d
save_dir = Path(file).parent if file else Path(dir)
@ -1019,7 +1019,7 @@ def plot_tune_results(csv_file="tune_results.csv"):
>>> plot_tune_results('path/to/tune_results.csv')
"""
import pandas as pd
import pandas as pd # scope for faster 'import ultralytics'
from scipy.ndimage import gaussian_filter1d
# Scatter plots for each hyperparameter