---
license: mit
tags:
- deepfake-detection
- video-classification
- efficientnet
- celeb df v2
pipeline_tag: video-classification
widget:
  - src: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/thumbnail.png
    example_title: "Sample Detection"
---

# Deepfake Video Classifier

🎬 **Detect manipulated videos with 95.73% accuracy**

This model analyzes video frames to determine if content is REAL or a DEEPFAKE. It is Trained on Celebdf v2 dataset and it uses efficientnet B-0. (https://www.kaggle.com/datasets/reubensuju/celeb-df-v2)
Developed by Sajjal Fatima, a Software Engineering student at Punjab University College of Information & Technology (PUCIT), Lahore, Pakistan.
## 🚀 Quick Start

```python
from model import DeepFakeModel
from utils import video_to_tensor

# Load model
model = DeepFakeModel("ffpp_efficientnet_best.pth")

# Process video
video_tensor = video_to_tensor("your_video.mp4")
result = model.predict(video_tensor)

print(f"Prediction: {result['prediction']}")  # REAL or FAKE
print(f"Confidence: {result['confidence']:.2%}")