🚀 ML Playground Dashboard An interactive Gradio app with mu
Identify inappropriate images in your uploads
Classify images into NSFW categories
Analyze files to detect NSFW content
Detect inappropriate images
Identify NSFW content in images
Detect people with masks in images and videos
Testing Transformers JS
Detect objects in images using 🤗 Transformers.js
Detect objects in images
Detect NSFW content in images
Detect deepfakes in videos, images, and audio
Detect AI watermark in images
ML Playground Dashboard is an interactive Gradio app designed to help users explore machine learning models for various tasks, including detecting harmful or offensive content in images. This dashboard provides a user-friendly interface where you can interact with different ML models, experiment with inputs, and visualize outputs in real time. It is a perfect tool for both beginners and developers looking to prototype and test ML models efficiently.
• Image Content Detection: Identify harmful or offensive content within images using pre-trained models. • Multiple Model Support: Experiment with different machine learning models for text, images, and speech. • Interactive Demos: Test models with sample inputs or upload your own data for experimentation. • Real-Time Results: Get immediate feedback and visualizations for your inputs. • User-Friendly Interface: Intuitive design that makes it easy to navigate and use even for non-experts.
What types of models are available on ML Playground Dashboard?
The dashboard supports image-based models for harmful content detection, as well as models for text analysis and speech processing. You can experiment with different models depending on your use case.
Can I upload custom images or text for testing?
Yes, you can upload your own images or input custom text to test the models. This feature allows you to see how the models perform with your specific data.
How do I interpret the results from the dashboard?
The results are displayed in a user-friendly format, with clear visualizations and classifications. For image models, you'll see predictions about the content, while text models may provide sentiment analysis or other relevant outputs.