Visualize how CNNs transform images into predictions

Explore layer-by-layer activations, feature maps, and Grad-CAM visualizations to understand what CNNs learn.

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Layer activations
Grad-CAM heatmaps
Prediction breakdown

Example CNN Explanation

See how a CNN transforms an image: from the original photo, through Grad-CAM heatmaps, to the final overlay visualization.

Step 1: Original
Original
Original image
Step 2: Overlay
Overlay
Grad-CAM overlay
Step 3: Grad-CAM
Grad-CAM
Grad-CAM heatmap
Prediction
Cat
94.2%

What You'll See

Explore every layer of a CNN's decision-making process

Feature Maps

See what each layer focuses on as the network processes your image through different levels of abstraction.

Grad-CAM

Understand why the model predicted that class with heatmap visualizations showing the most important regions.

Prediction Breakdown

Track confidence scores and explore the top predicted classes with detailed probability breakdowns.

Choose a Model

Select a pre-trained CNN model to analyze your images

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Get Started

Upload an image and analyze it with your selected model

Upload Image

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How It Works

Understand the process from image upload to visualization

1

Upload Image

Upload any image you want to analyze.

2

CNN Processing

The CNN extracts features through multiple layers.

3

Visualization

Explore feature maps and Grad-CAM heatmaps.

4

Prediction

View the final prediction with confidence scores.