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907462b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | import matplotlib.pyplot as plt
import numpy as np
def example_data():
data = [
# ('NoC@80%', [
# [1.36, 1.30, 2.82, 1.75, 2.62, 5.52, 2.15, 13.50, 1.77],
# [0 for _ in range(9)],
# [1.56, 1.56, 3.19, 2.41, 3.41, 6.10, 3.35, 13.31, 2.48],
# [0 for _ in range(9)],
# [0 for _ in range(9)]]),
('NoC@85%', [
[1.36, 1.40, 3.79, 1.94, 3.47, 7.18, 2.80, 16.38, 2.05],
[0 for _ in range(9)],
[1.70, 1.83, 4.41, 2.71, 4.46, 7.76, 4.05, 16.71, 2.90],
[0 for _ in range(9)],
[0 for _ in range(9)]]),
('NoC@90%', [
[1.50, 2.08, 5.11, 2.25, 5.54, 10.82, 5.55, 19.17, 2.79],
[0 for _ in range(9)],
[1.92, 2.79, 6.08, 3.17, 6.79, 11.24, 6.20, 19.09, 3.80],
[0 for _ in range(9)],
[0 for _ in range(9)]])
]
return data
if __name__ == '__main__':
N = 9
models = ('SOTA', 'ViT-B-224', 'Vit-B-448', 'ViT-L-224', 'ViT-L-448')
num_models = len(models)
colors = ('#1aaf6c', '#429bf4', '#d42cea', '#feea11', '#00ffff')
datasets = ['GrabCut', 'Berkeley', 'DAVIS', 'Pascal', 'SBD', 'BraTS', 'ssTEM', 'OAI-ZIB', 'COCO_MVal']
num_datasets = len(datasets)
angles = np.linspace(0, 2 * np.pi, num_datasets, endpoint=False).tolist()
angles += angles[:1]
fig, axs = plt.subplots(figsize=(12, 6), nrows=1, ncols=2, subplot_kw=dict(polar=True))
fig.subplots_adjust(wspace=0.5, hspace=0.05, top=0.85, bottom=0.05)
def add_to_radar(label, values, color, alpha=0.25):
values += values[:1]
ax.plot(angles, values, color=color, linewidth=1, label=label)
ax.fill(angles, values, color=color, alpha=alpha)
metric_data = example_data()
for ax, (metric, data) in zip(axs.flat, metric_data):
# add each model to the chart
for i, model in enumerate(models):
values = data[i]
add_to_radar(models[i], values, color=colors[i])
ax.set_title(metric, weight='bold', size='medium', position=(0.5, 1.1),
horizontalalignment='center', verticalalignment='center')
ax.set_theta_offset(np.pi / 2)
ax.set_theta_direction(-1)
ax.set_thetagrids(np.degrees(angles[:-1]), datasets)
# Go through labels and adjust alignment based on where
# it is in the circle.
for label, angle in zip(ax.get_xticklabels(), angles):
if angle in (0, np.pi):
label.set_horizontalalignment('center')
elif 0 < angle < np.pi:
label.set_horizontalalignment('left')
else:
label.set_horizontalalignment('right')
ax.set_ylim(0, 20)
# Add some custom styling.
# Change the color of the tick labels.
ax.tick_params(colors='#222222')
# Make the y-axis (0-100) labels smaller.
ax.tick_params(axis='y', labelsize=8)
# Change the color of the circular gridlines.
ax.grid(color='#AAAAAA')
# Change the color of the outermost gridline (the spine).
ax.spines['polar'].set_color('#222222')
# Change the background color inside the circle itself.
ax.set_facecolor('#FAFAFA')
axs[0].legend(loc=(1.1, 0.95))
# axs[0].legend(loc=(1.2, 0.95), labelspacing=0.1, fontsize='small')
# fig.text(0.5, 0.965, 'Comparison Results',
# horizontalalignment='center', color='black', weight='bold',
# size='large')
plt.show() |