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import matplotlib.pyplot as plt
import numpy as np
import os
def load_data(filename):
pts = []
f = open(filename, "rb")
for line in f:
pts.append(float(line.strip()))
f.close()
return pts
dataset = 'spinal'
weights_path = 'weights_'+dataset
###############################################
# Load data
train_pts = load_data(os.path.join(weights_path, 'train_loss.txt'))
val_pts = load_data(os.path.join(weights_path, 'val_loss.txt'))
def draw_loss():
x = np.linspace(0, len(train_pts), len(train_pts))
plt.plot(x,train_pts,'ro-',label='train')
plt.plot(x,val_pts,'bo-',label='val')
# plt.axis([0, 50, 9.25, 11])
plt.legend(loc='upper right')
plt.xlabel('Epochs')
plt.ylabel('Loss')
plt.show()
def draw_loss_ap():
ap05_pts = load_data(os.path.join(weights_path, 'ap_05_list.txt'))
ap07_pts = load_data(os.path.join(weights_path, 'ap_07_list.txt'))
x = np.linspace(0,len(train_pts),len(train_pts))
x1 = np.linspace(0, len(train_pts), len(ap05_pts))
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('Epochs')
ax1.set_ylabel('Loss', color=color)
ax1.plot(x, train_pts, 'ro-',label='train')
ax1.plot(x, val_pts, 'bo-',label='val')
ax1.tick_params(axis='y', labelcolor=color)
plt.legend(loc = 'lower right')
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('AP', color=color) # we already handled the x-label with ax1
ax2.plot(x1, ap05_pts, 'go-',label='AP@05')
ax2.plot(x1, ap07_pts, 'yo-', label='AP@07')
ax2.tick_params(axis='y', labelcolor=color)
fig.tight_layout() # otherwise the right y-label is slightly clipped
plt.legend(loc = 'upper right')
plt.show()
if __name__ == '__main__':
draw_loss()
# draw_loss_ap() |