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训练集分为3类,请问这三类指的是哪三类 #93

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ZZ-QTD opened this issue Apr 26, 2022 · 2 comments
Open

训练集分为3类,请问这三类指的是哪三类 #93

ZZ-QTD opened this issue Apr 26, 2022 · 2 comments

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@ZZ-QTD
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ZZ-QTD commented Apr 26, 2022

深度截图_选择区域_20220426143159
0:我可以理解为真人脸,
1:为假人脸
2:代表着什么呢

@weihualiuhupituzi
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电子攻击 和其他方式攻击两类

@hozhiyi
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hozhiyi commented Feb 22, 2024

根据test.py里所写的,

label = np.argmax(prediction)
value = prediction[0][label]/2
if label == 1:
    print("Image '{}' is Real Face. Score: {:.2f}.".format(image_name, value))
    result_text = "RealFace Score: {:.2f}".format(value)
    color = (255, 0, 0)
else:
    print("Image '{}' is Fake Face. Score: {:.2f}.".format(image_name, value))
    result_text = "FakeFace Score: {:.2f}".format(value)
    color = (0, 0, 255)
print("Prediction cost {:.2f} s".format(test_speed))

得出结论1应是真人脸,而0和2分别为不同的攻击类别。在作者提供的sample里只有影印电子攻击的例子,所以0和2应该分别就是它们了。

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