| import numpy as np |
| from tensorflow.keras.models import load_model |
| from data_loader import load_images_from_folder, create_sequences |
|
|
| def predict_next_frame(model_path, input_sequence): |
| model = load_model(model_path) |
| predictions = model.predict(input_sequence) |
| return predictions |
|
|
| if __name__ == "__main__": |
| folder_path = "/path/to/new/data" |
| img_size = (200, 200) |
| sequence_length = 5 |
|
|
| |
| dataset = load_images_from_folder(folder_path, img_size=img_size) |
| dataset = np.expand_dims(dataset, axis=-1) |
| sequences = create_sequences(dataset, sequence_length) |
|
|
| |
| model_path = "best_model.keras" |
| predictions = predict_next_frame(model_path, sequences) |
| print("Predictions generated for the input sequence.") |
|
|
