📸 Image Classification Demo
Build and train your own image classifier with interactive examples
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CNN Architecture Builder
What is Image Classification?
Image classification is the task of assigning a label to an image from a predefined set of categories. It's one of the fundamental tasks in computer vision and powers countless applications.
🎯 Real-World Applications
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Medical imaging: Detecting diseases in X-rays and MRIs
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Autonomous vehicles: Recognizing traffic signs and pedestrians
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Social media: Auto-tagging photos and content moderation
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E-commerce: Visual search and product recommendations
📷
Input
Raw pixel values from an image (e.g., 224×224×3)
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Processing
CNN extracts features and learns patterns
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Output
Probabilities for each class (e.g., 85% cat)
🔄 The Classification Pipeline
1
Preprocessing
Resize, normalize, augment
2
Feature Extraction
CNN layers detect edges, textures, patterns
3
Classification
Dense layers output class probabilities
4
Prediction
Select class with highest probability
📊 Popular Datasets
ImageNet
1.4M images, 1,000 classes
CIFAR-10
60K images, 10 classes
MNIST
70K handwritten digits
Fashion-MNIST
70K clothing items