neuroviz-keras 0.1.0

Real-time neural network weight visualizer for TensorFlow/Keras training

🧠 NeuroViz

Real-time neural network weight visualizer for TensorFlow/Keras training.

Stop guessing what's happening inside your model. NeuroViz gives you a live web dashboard that shows the actual weight values of every neuron while training — not just loss and accuracy.

✨ Features

• 🔴 Live Grayscale Neuron Map — Neurons glow from black (near-zero) to white (high magnitude), giving you an instant X-ray of your network
• 🗺️ Weight Heatmaps — Click any layer to see its full weight matrix as a color-coded heatmap
• 📊 Weight Distributions — Live histograms showing how weight values are distributed per layer
• 📈 Training Metrics — Loss and accuracy curves updated in real time
• ⏱️ Epoch Timeline — Scrub through past epochs to see how weights evolved
• ⚡ Zero Config — Just add one callback, dashboard opens automatically

🚀 Installation

pip install neuroviz

📖 Usage

from neuroviz import NeuroViz

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])

# Just add the callback — that's it!
model.fit(x_train, y_train,
          epochs=20,
          validation_data=(x_val, y_val),
          callbacks=[NeuroViz()])

The dashboard will automatically open at http://localhost:5050.

Options

NeuroViz(
    port=5050,           # Web server port (default: 5050)
    open_browser=True,   # Auto-open browser (default: True)
    update_freq='epoch', # Update frequency: 'epoch' or 'batch' (default: 'epoch')
)

🖼️ What You'll See

A dark-themed, premium dashboard with:

1. Network Diagram — Interactive visualization of your model architecture. Each neuron is colored on a grayscale: black = weight near zero, white = high weight magnitude.
2. Layer Inspector — Click on any layer to see a heatmap of all its weights.
3. Distribution Panel — Histograms of weight values for each layer.
4. Metrics Chart — Live loss and accuracy curves.

📋 Requirements

• Python >= 3.8
• TensorFlow >= 2.0

📄 License

MIT