Unverified 提交 685d6013 authored 作者: Glenn Jocher's avatar Glenn Jocher 提交者: GitHub

Increase plot_labels() speed (#1736)

上级 49abc722
...@@ -205,7 +205,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None): ...@@ -205,7 +205,7 @@ 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:
Thread(target=plot_labels, args=(labels, save_dir, loggers), daemon=True).start() plot_labels(labels, save_dir, loggers)
if tb_writer: if tb_writer:
tb_writer.add_histogram('classes', c, 0) tb_writer.add_histogram('classes', c, 0)
......
...@@ -11,6 +11,8 @@ import cv2 ...@@ -11,6 +11,8 @@ import cv2
import matplotlib import matplotlib
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import pandas as pd
import seaborn as sns
import torch import torch
import yaml import yaml
from PIL import Image, ImageDraw from PIL import Image, ImageDraw
...@@ -253,34 +255,24 @@ def plot_study_txt(path='', x=None): # from utils.plots import *; plot_study_tx ...@@ -253,34 +255,24 @@ def plot_study_txt(path='', x=None): # from utils.plots import *; plot_study_tx
def plot_labels(labels, save_dir=Path(''), loggers=None): def plot_labels(labels, save_dir=Path(''), loggers=None):
# plot dataset labels # plot dataset labels
print('Plotting labels... ')
c, b = labels[:, 0], labels[:, 1:].transpose() # classes, boxes c, b = labels[:, 0], labels[:, 1:].transpose() # classes, boxes
nc = int(c.max() + 1) # number of classes nc = int(c.max() + 1) # number of classes
colors = color_list() colors = color_list()
x = pd.DataFrame(b.transpose(), columns=['x', 'y', 'width', 'height'])
# seaborn correlogram # seaborn correlogram
try: sns.pairplot(x, corner=True, diag_kind='auto', kind='hist', diag_kws=dict(bins=50), plot_kws=dict(pmax=0.9))
import seaborn as sns
import pandas as pd
x = pd.DataFrame(b.transpose(), columns=['x', 'y', 'width', 'height'])
sns.pairplot(x, corner=True, diag_kind='hist', kind='scatter', markers='o',
plot_kws=dict(s=3, edgecolor=None, linewidth=1, alpha=0.02),
diag_kws=dict(bins=50))
plt.savefig(save_dir / 'labels_correlogram.jpg', dpi=200) plt.savefig(save_dir / 'labels_correlogram.jpg', dpi=200)
plt.close() plt.close()
except Exception as e:
pass
# matplotlib labels # matplotlib labels
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_xlabel('classes') ax[0].set_xlabel('classes')
ax[2].scatter(b[0], b[1], c=hist2d(b[0], b[1], 90), cmap='jet') sns.histplot(x, x='x', y='y', ax=ax[2], bins=50, pmax=0.9)
ax[2].set_xlabel('x') sns.histplot(x, x='width', y='height', ax=ax[3], bins=50, pmax=0.9)
ax[2].set_ylabel('y')
ax[3].scatter(b[2], b[3], c=hist2d(b[2], b[3], 90), cmap='jet')
ax[3].set_xlabel('width')
ax[3].set_ylabel('height')
# rectangles # rectangles
labels[:, 1:3] = 0.5 # center labels[:, 1:3] = 0.5 # center
......
Markdown 格式
0%
您添加了 0 到此讨论。请谨慎行事。
请先完成此评论的编辑!
注册 或者 后发表评论