Detect Kermit is a Python machine learning project that trains a binary image classifier to identify whether Kermit the Frog from The Muppets TV show appears in a given image or video frame. It uses ImageAI’sDocumentation Index
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CustomImagePrediction (ResNet architecture) on top of TensorFlow, and supports inference on both static images and full video files.
Introduction
Understand how the project works, its architecture, and what you can do with it.
Quickstart
Install dependencies, load the pre-trained model, and run your first prediction in minutes.
Training Guide
Train or retrain the ResNet model on your own dataset of Kermit and non-Kermit images.
Prediction Guide
Run predictions on images and video files using the command-line interface.
How It Works
Prepare your dataset
Collect and organise training images into
kermit and no-kermit folders. Use the helper scripts to extract frames from video, rotate images for augmentation, and download extra images from Google.Train the model
Run
imageai_build_model.py to train a ResNet model using ImageAI’s CustomImagePrediction. The trained weights are saved as kermit_finder.h5.A pre-trained model (
data/images/models/kermit_finder.h5) and class map (data/images/json/model_class.json) are included in the repository via Git LFS, so you can run predictions without retraining.