zsxkib / emotion2color

Transform your text into a beautiful two-tone color gradient that represents your emotions.

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Input

Output

Run time and cost

This model runs on CPU hardware. Predictions typically complete within 78 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Emotion Visualization: Paint Your Mood with Color! 🌈

Transform a sentence into vibrant colors representing emotions with our tool. Let us guide you through the journey from text to radiant color gradients. 🎨

The Mechanics of It All 🤔

Our Python-based Cog Predictor effortlessly converts your textual input into captivating color gradients. Here’s how it works: - Your text is received, no matter its content. - Our model, distilroberta-base by j-hartmann, adeptly uncovers the emotional sentiments within your text. - These detected emotions are then converted into colors, forming a visual representation as intricate as your feelings.

Translating Emotions into Radiant Gradients 🎨

The model recognizes a range of emotions: anger 🤬, disgust 🤢, fear 😨, joy 😀, neutral 😐, sadness 😭, and surprise 😲. Each emotion corresponds to a unique color, forming a comprehensive palette to paint your emotional landscape. The intensity of the detected emotions influences the transition points within the gradient. The stronger the emotion, the more it shapes the color scheme.

Your Journey to Emotion Visualization 🚀

To experience the emotion visualization, follow these simple steps: 1. Provide your text in the text box. 2. Click the “Run” button. 3. The output image will appear, reflecting the emotional sentiment of your input text as a radiant gradient.

Prediction Output