Comments (1)
Thanks for your interest.
First, import matplotlib.pyplot as plt
Then, calculate the score of in-distribution samples as Score_ID and calculate the score of out-of-distribution samples as Score_OOD.
At last, plot the histogram as:
n1, bins1, patches1 = plt.hist(Score_ID,bins=100,density=True,color='orange',alpha=0.) plt.fill_between(bins1[:-1], n1, color='orange', alpha=1.0,label="ID") plt.plot(bins1[:-1],n1,'--',color='coral')
n2, bins2, patches2 = plt.hist(Score_OOD,bins=100,density=True,color='lightgreen',alpha=0.) plt.fill_between(bins2[:-1], n2, color='lightgreen', alpha=0.8,label="OOD") plt.plot(bins2[:-1],n2,'--',color='green')
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Related Issues (19)
- Some questions! HOT 2
- Can you provide the training code for DRA please? HOT 1
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- I could provide some pretrained model HOT 1
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- [Submit Model] <convnext_L>
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