| import tensorflow as tf | |
| from tensorflow.keras.preprocessing import image | |
| import numpy as np | |
| import json | |
| def predict_breed(img_path): | |
| model = tf.keras.models.load_model("dog_breed_classifier.h5") | |
| with open("class_indices.json", "r") as f: | |
| class_indices = json.load(f) | |
| class_names = {v: k for k, v in class_indices.items()} | |
| img = image.load_img(img_path, target_size=(224, 224)) | |
| img_array = image.img_to_array(img) / 255.0 | |
| img_array = np.expand_dims(img_array, axis=0) | |
| prediction = model.predict(img_array) | |
| predicted_class = class_names[np.argmax(prediction)] | |
| print(f"Predicted Dog Breed: {predicted_class}") | |
| predict_breed(r"E:\Dog_Breed_Classification_model\dataset\Akita_Inu\Akita_Inu1.jpg") |