https://github.com/calcuis/ai-recognizor-py
https://github.com/calcuis/ai-recognizor-py
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/calcuis/ai-recognizor-py
- Owner: calcuis
- Created: 2023-11-27T01:04:21.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-27T23:14:35.000Z (over 1 year ago)
- Last Synced: 2025-01-21T13:11:49.632Z (5 months ago)
- Language: Python
- Size: 1.65 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## ai recognizor
This Python code defines a simple graphical user interface (GUI) application for image classification using a pre-trained convolutional neural network (CNN) model. The code utilizes the `taipy.gui` library for GUI components, PIL (Pillow) for image processing, and tensorflow for loading a pre-trained image classification model.
Here's a breakdown of the code:
Import necessary libraries:
- Gui from `taipy.gui` for creating the GUI.
- Image from PIL for working with images.
- `tensorflow` for loading and using a pre-trained neural network model.
- `numpy` for numerical operations.
Define a dictionary `class_names` mapping class indices to corresponding class labels.
Load a pre-trained neural network model using TensorFlow's Keras API. The model is loaded from a file named "baseline.keras."
Define a function `predict_image` that takes the loaded model and the path to an image as input, processes the image, and returns the top probability and predicted class label.
Set up initial variables (`content`, `img_path`, `prob`, `pred`) and define an HTML-like string index, which represents the structure of the GUI. It includes a file selector, an image display, a probability indicator, and a text field for displaying the predicted class.
Define a callback function `on_change` that is triggered when the selected image changes. This function uses the `predict_image` function to obtain the prediction results and updates the GUI state accordingly.
Create a GUI application (Gui object) with the specified structure (`index`) and set the on_change function as the callback for changes in the file selector.
Run the GUI application when the script is executed directly (`__name__ == "__main__"`). The application allows users to select an image file, displays the selected image, and provides a prediction of the image class along with the probability.
Note: The GUI structure (`index`) is defined using a custom syntax (`<|...|>`) provided by the taipy.gui library. The `app.run`(`use_reloader=True`) line runs the GUI application, and `use_reloader=True` enables automatic reloading of the application when the source code changes.