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labels.jpg class names (#2454)

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* labels.png class names

* fontsize=10
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Glenn Jocher 2021-03-12 22:15:41 -08:00 committed by GitHub
parent f4197214aa
commit 08d4918d7f
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2 changed files with 8 additions and 3 deletions
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2
train.py
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@ -203,7 +203,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
# cf = torch.bincount(c.long(), minlength=nc) + 1. # frequency # cf = torch.bincount(c.long(), minlength=nc) + 1. # frequency
# model._initialize_biases(cf.to(device)) # model._initialize_biases(cf.to(device))
if plots: if plots:
plot_labels(labels, save_dir, loggers) plot_labels(labels, names, save_dir, loggers)
if tb_writer: if tb_writer:
tb_writer.add_histogram('classes', c, 0) tb_writer.add_histogram('classes', c, 0)

7
utils/plots.py
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@ -269,7 +269,7 @@ def plot_study_txt(path='', x=None): # from utils.plots import *; plot_study_tx
plt.savefig(str(Path(path).name) + '.png', dpi=300) plt.savefig(str(Path(path).name) + '.png', dpi=300)
def plot_labels(labels, save_dir=Path(''), loggers=None): def plot_labels(labels, names=(), save_dir=Path(''), loggers=None):
# plot dataset labels # plot dataset labels
print('Plotting labels... ') print('Plotting labels... ')
c, b = labels[:, 0], labels[:, 1:].transpose() # classes, boxes c, b = labels[:, 0], labels[:, 1:].transpose() # classes, boxes
@ -286,6 +286,11 @@ def plot_labels(labels, save_dir=Path(''), loggers=None):
matplotlib.use('svg') # faster matplotlib.use('svg') # faster
ax = plt.subplots(2, 2, figsize=(8, 8), tight_layout=True)[1].ravel() ax = plt.subplots(2, 2, figsize=(8, 8), tight_layout=True)[1].ravel()
ax[0].hist(c, bins=np.linspace(0, nc, nc + 1) - 0.5, rwidth=0.8) ax[0].hist(c, bins=np.linspace(0, nc, nc + 1) - 0.5, rwidth=0.8)
ax[0].set_ylabel('instances')
if 0 < len(names) < 30:
ax[0].set_xticks(range(len(names)))
ax[0].set_xticklabels(names, rotation=90, fontsize=10)
else:
ax[0].set_xlabel('classes') ax[0].set_xlabel('classes')
sns.histplot(x, x='x', y='y', ax=ax[2], bins=50, pmax=0.9) sns.histplot(x, x='x', y='y', ax=ax[2], bins=50, pmax=0.9)
sns.histplot(x, x='width', y='height', ax=ax[3], bins=50, pmax=0.9) sns.histplot(x, x='width', y='height', ax=ax[3], bins=50, pmax=0.9)