2.Understanding and Using ANN : Identifying age group of an actor

 Design Artificial Neural Networks for Identifying and Classifying an actor using Kaggle Dataset.

COLAB

from tensorflow.keras.models import load_model

from PIL import Image

import numpy as np

image_height = 128

image_width = 128

num_channels = 3

# Load the trained model

model = load_model('/content/drive/MyDrive/trained_model_NEW_2_2_Dataset.h5')  # Replace 'your_trained_model.h5' with the actual file name

# Read the new face image

new_face_path = '/content/drive/MyDrive/2_Predict/a.jpg'  # Replace 'path_to_new_face.jpg' with the actual file path

new_face = Image.open(new_face_path)

#new_face.show()

display(new_face)

# Preprocess the image

new_face = new_face.resize((image_width, image_height))

new_face = np.array(new_face)

#new_face = new_face.astype('float32') / 255.0

new_face = np.expand_dims(new_face, axis=0)  # Add a batch dimension

# Perform prediction

predictions = model.predict(new_face)

predicted_age_group = np.argmax(predictions)

print("predictions are ",predictions)

print("Predicted Age Group:", predicted_age_group)

# Map the predicted age group index to the actual label

age_mapping = {0: 'YOUNG', 1: 'MIDDLE', 2: 'OLD'}  # Update with your age group labels mapping

predicted_age_group_label = age_mapping[predicted_age_group]

print("Predicted Age Group:", predicted_age_group_label)

MODEL:

https://drive.google.com/file/d/1RKTVY7JLgL35D4dFQ_2YZRFMC7ntSUvG/view?usp=sharing

IMAGES:

https://drive.google.com/drive/folders/1xhQJSzL_OL72YXBgdQD10_JmYpHPngLu?usp=sharing

Design Artificial Neural Networks for Identifying and Classifying an actor using Kaggle Dataset.