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53 lines
1.2 KiB
53 lines
1.2 KiB
2 years ago
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# Deepfake
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*author: Zhuoran Yu*
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<br />
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## Description
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Deepfake techniques, which present realistic AI-generated videos of people doing and saying fictional things, have the potential to have a significant impact on how people determine the legitimacy of information presented online.
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This operator predicts the probability of a fake video for a given video.This is an adaptation from [DeepfakeDetection](https://github.com/smu-ivpl/DeepfakeDetection).
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<br />
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## Code Example
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Load videos from path '/home/test_video'
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and use deepfake operator to predict the probabilities of fake videos.
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```python
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import towhee
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(
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towhee.glob['path']('/home/test_video')
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.deepfake['path', 'scores']()
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.select['path', 'scores']()
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.show()
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)
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```
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<img src="./deepfake.png" height="100px"/>
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```shell
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[0.9893, 0.9097]
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```
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<br />
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## Interface
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A deepfake operator takes videos' paths as input.
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It predicts the probabilities of fake videos.The higher the score, the higher the probability of it being a fake video.(It can be considered to be a fake video with score higher than 0.5)
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**Parameters:**
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***filepath:*** *str*
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Absolute address of the test videos.
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**Returns:** *list*
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The probabilities of videos being fake ones.
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