Metadata-Version: 2.1
Name: Deep Fake Detection
Version: 0.0.7
Summary: Deep Fake Detection Project
Home-page: https://github.com/MohamedSebaie/DeepFake-Detection-Using-Pytorch
Author: Mohamed Sebaie
Author-email: mohamedsebaie1@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENCE


 

<h1 color="green"><b>Deep Fake Detection Package</b></h1>

---

<h1 color="green"><b>Abstract</b></h1>
<p>This project Deepfakes can distort our perception of the truth and we need to develop a strategy to improve their detection. Deep Fakes are increasingly detrimental to privacy, social security, and democracy. We plan to achieve better accuracy in predicting real and fake videos..</p>


<h1 color="green"><b>Instructions to Install our Deep Fake Detection Package</b></h1>


1. Install:

```python
pip install Deep-Fake-Detection
```

2. Download the Finetunned Model Weights

```python
import gdown
ResNextModelURL    = 'https://drive.google.com/uc?id=1siAcM9uTEoLEeqKFxq5h-hjs4NoHS0SU'
XcePtionModelURL   = 'https://drive.google.com/uc?id=1--68J6Ipny937AFjJ_AKjhFXFnvnGecV'
ResNextModel    = 'resnext.pth'
XcePtionModel   = 'xception.pth'

gdown.download(ResNextModelURL, ResNextModel, quiet=False)
gdown.download(XcePtionModelURL, XcePtionModel, quiet=False)
```
3. Import the DeepFake_Utils from deepfake_detection :

```python
from deepfake_detection import DeepFake_Utils
```

4. Detect Detect the video is fake or not by Ensemble ResNext and Inception Custom Models :

```python
# Run the Below Function by Input your Video Path to get the outPutVideo with Label Fake on Real on it
DeepFake_Utils.Inference_on_video(OutputVideoPath,InputVideoPath)


# Show the Video
VideoFileClip(OutputVideoPath, audio=False, target_resolution=(300,None)).ipython_display()
```

