This model is a specialized image classification model trained to identify World of Warcraft (WoW) spell images. It accepts a 56x56 pixel image as input and outputs the probabilities for various spell IDs.
The WOW Spell Identifier is designed to assist gamers by automating the recognition of spell icons during gameplay. By processing 56x56 pixel images, the model predicts the likelihood of each spell ID, enabling the integration of this functionality into gaming tools for acessibility.
The model can be integrated into gaming interfaces or used in standalone applications to enhance the gaming experience by providing real-time spell identification.
1import tensorflow as tf
2
3# Load the trained model
4model = tf.keras.models.load_model('path_to_model/spell_identifier_model.h5')
5
6# Load the list of spell IDs from classes.txt
7with open('path_to_classes/classes.txt', 'r') as file:
8 classes = file.read().splitlines()
9
10# Function to preprocess the input image
11def preprocess_image(image_path):
12 # Implement preprocessing steps (e.g., resizing, normalization)
13 pass
14
15# Function to predict the spell ID
16def predict_spell_id(image_path):
17 processed_image = preprocess_image(image_path)
18 predictions = model.predict(processed_image)
19 predicted_class_index = np.argmax(predictions)
20 predicted_spell_id = classes[predicted_class_index]
21 return predicted_spell_id
22
23# Example usage
24spell_id = predict_spell_id('path_to_image/spell_image.png')
25print(spell_id)
In this example, classes.txt contains the list of spell IDs corresponding to the model’s output classes. The predict_spell_id function processes the image, makes a prediction, and then maps the predicted class index to the actual spell ID using the classes list.
Contributions to the model and its development are welcome.
This project is licensed under the MIT License.
