metadata
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
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%}")