|
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() |