updates
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@ -442,12 +442,28 @@ def plot_results():
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import matplotlib.pyplot as plt
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plt.figure(figsize=(16, 8))
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s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP']
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for f in ('results_d5.txt', 'results_d10.txt', 'results_new.txt',
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for f in ('results.txt',
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):
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results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 7, 8, 9, 10]).T # column 16 is mAP
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for i in range(9):
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results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 7, 8, 17, 18, 16]).T # column 16 is mAP
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for i in range(10):
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plt.subplot(2, 5, i + 1)
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plt.plot(results[i, :250], marker='.', label=f)
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plt.title(s[i])
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if i == 0:
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plt.legend()
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# def plot_results():
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# # Plot YOLO training results file 'results.txt'
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# import numpy as np
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# import matplotlib.pyplot as plt
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# plt.figure(figsize=(16, 8))
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# s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP']
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# for f in ('results_d5.txt', 'results_d10.txt', 'results_64.txt',
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# ):
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# results = np.loadtxt(f, usecols=[16]).T # column 16 is mAP
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# for i in range(1):
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# plt.subplot(2, 5, i + 1)
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# plt.plot(results, marker='.', label=f)
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# plt.title(s[i])
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# if i == 0:
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# plt.legend()
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