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Fix ClearML Mosaic callback to 'on_train_epoch_end' (#92)

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Glenn Jocher 2022-12-25 17:04:24 +01:00 • committed by GitHub
parent 0298821467
commit 249dfbdc05
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5 changed files with 17 additions and 24 deletions
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10
ultralytics/yolo/utils/metrics.py
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@ -343,7 +343,7 @@ def compute_ap(recall, precision):
return ap, mpre, mrec
def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir='.', names=(), eps=1e-16, prefix=""):
def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir=Path(), names=(), eps=1e-16, prefix=""):
""" Compute the average precision, given the recall and precision curves.
Source: https://github.com/rafaelpadilla/Object-Detection-Metrics.
# Arguments
@ -398,10 +398,10 @@ def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir='.', names
names = [v for k, v in names.items() if k in unique_classes] # list: only classes that have data
names = dict(enumerate(names)) # to dict
if plot:
plot_pr_curve(px, py, ap, Path(save_dir) / f'{prefix}PR_curve.png', names)
plot_mc_curve(px, f1, Path(save_dir) / f'{prefix}F1_curve.png', names, ylabel='F1')
plot_mc_curve(px, p, Path(save_dir) / f'{prefix}P_curve.png', names, ylabel='Precision')
plot_mc_curve(px, r, Path(save_dir) / f'{prefix}R_curve.png', names, ylabel='Recall')
plot_pr_curve(px, py, ap, save_dir / f'{prefix}PR_curve.png', names)
plot_mc_curve(px, f1, save_dir / f'{prefix}F1_curve.png', names, ylabel='F1')
plot_mc_curve(px, p, save_dir / f'{prefix}P_curve.png', names, ylabel='Precision')
plot_mc_curve(px, r, save_dir / f'{prefix}R_curve.png', names, ylabel='Recall')
i = smooth(f1.mean(0), 0.1).argmax() # max F1 index
p, r, f1 = p[:, i], r[:, i], f1[:, i]