Ankle/yolov5_birdproject
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Update on_train_end callback (#7716)

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Glenn Jocher authored and GitHub committed 2022-05-05 21:25:13 -07:00
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train.py
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@@ -466,7 +466,6 @@ def train(hyp, opt, device, callbacks): # hyp is path/to/hyp.yaml or hyp dictio
callbacks.run('on_fit_epoch_end', list(mloss) + list(results) + lr, epoch, best_fitness, fi) callbacks.run('on_fit_epoch_end', list(mloss) + list(results) + lr, epoch, best_fitness, fi)
callbacks.run('on_train_end', last, best, plots, epoch, results) callbacks.run('on_train_end', last, best, plots, epoch, results)
LOGGER.info(f"Results saved to {colorstr('bold', save_dir)}")
torch.cuda.empty_cache() torch.cuda.empty_cache()
return results return results
utils/loggers/__init__.py
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@@ -164,6 +164,7 @@ class Loggers():
plot_results(file=self.save_dir / 'results.csv') # save results.png plot_results(file=self.save_dir / 'results.csv') # save results.png
files = ['results.png', 'confusion_matrix.png', *(f'{x}_curve.png' for x in ('F1', 'PR', 'P', 'R'))] files = ['results.png', 'confusion_matrix.png', *(f'{x}_curve.png' for x in ('F1', 'PR', 'P', 'R'))]
files = [(self.save_dir / f) for f in files if (self.save_dir / f).exists()] # filter files = [(self.save_dir / f) for f in files if (self.save_dir / f).exists()] # filter
self.logger.info(f"Results saved to {colorstr('bold', self.save_dir)}")
if self.tb: if self.tb:
for f in files: for f in files: