Project Info
This project did not submit a demo video on Devpost.
Inspiration
Fascinated by the power of artificial intelligence in media, we were inspired to create a deepfaking app to explore the boundaries between reality and digital innovation. Our goal was to not only showcase the potential of AI in creating hyper-realistic content but also to raise awareness about the ethical implications and need for responsible use of such powerful technology.
What it does
Out web-app detect deepfakes and to provide a critical tool for verifying the authenticity of digital media. This not helps to combat the spread of misinformation and protect personal reputations, but it also serves as a frontline defense in maintaining the integrity of online content
How we built it
We created a video splitter in python, which splits the video into multiple frames. Each frame is then sent through our AI model which detects any inaccuracies in the facial expression of the video. The AI model utilizes neural networks and maseonet class with tenserflow to analyze if it was created with deepfake technology.
Challenges we ran into
We ran into many challeneges throughout the processs of developing our code however, the ones that were the most challening were finding the right dataset to use and training the AI to get the most accurate results.
Accomplishments we're proud of
We are proud to have developed a program that is highly effective and accurate when categorizing and detecting deepfake technology.
This repository has no readme, or GitHub could not be reached.
Analysis
View
Metric
- 3
- 2
- 1
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- HTMLIn code
- PythonIn code
- JavaScriptClaimed
2 of 3 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
29 KB
Source files
9
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
RithvikIlluri/cruzhacks2024
18 files · 34.9 MB · @ 7a6f9ca
Structure
Interface
8 files · 44%Screens, components and styles rendered to the user.
Application logic
2 files · 11%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- HTML89%
- Python11%
Share of indexed source by file size. Binary and vendored files are excluded.
This project’s features have not been analysed yet.
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