| import os | |
| os.system("pip install tensorflow") | |
| import gradio as gra | |
| import numpy as np | |
| import keras | |
| model = keras.models.load_model("text2seed-model") | |
| max_sequence_length = 1000 | |
| def podgotovka(text_input): | |
| text_input_encoded = [ord(char) for char in text_input.lower()] | |
| padded_input = np.zeros((1, max_sequence_length), dtype=np.int) | |
| padded_input[0, :len(text_input_encoded)] = text_input_encoded | |
| return padded_input | |
| def get_seed(text_input): | |
| padded_input = podgotovka(text_input) | |
| seed = model.predict(padded_input) | |
| seed = int(str(seed[0][0]).replace("0.", "")) | |
| print(seed) | |
| return seed | |
| def text2seed(text_input): | |
| return str(get_seed(text_input)) | |
| def text2randint(text_input): | |
| np.random.seed(get_seed(text_input)) | |
| number = np.random.randint(1, 10) | |
| return str(number) | |
| def text2random(text_input): | |
| np.random.seed(get_seed(text_input)) | |
| number = np.random.random() | |
| return str(number) | |
| text2seed_interface = gra.Interface(fn = text2seed, inputs="text", outputs="text") | |
| text2randint_interface = gra.Interface(fn = text2randint, inputs="text", outputs="text") | |
| text2random_interface = gra.Interface(fn = text2random, inputs="text", outputs="text") | |
| app = gra.Blocks() | |
| with app: | |
| gra.Markdown(""" | |
| # Welcome to the text2seed! | |
| Select the mode, enter text in text_input and enjoy the result! | |
| """) | |
| gra.TabbedInterface([text2seed_interface, text2randint_interface, text2random_interface], ["text2seed", "text2randint", "text2random"]) | |
| app.launch() |