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import gradio as gr
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import tensorflow as tf
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from SpaceGen_preprocessing import *
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from utils import *
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model_path = "SpaceGen_Large.keras"
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model = tf.keras.models.load_model(model_path)
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def fix_space(text):
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text = clean_sentence(text)
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X = text_to_X(text)
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predictions = model.predict(X, verbose=0)
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predicted_labels = []
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for pred in predictions[0]:
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predicted_labels.append(1 if pred[1] > .5 else 0)
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fixed_text = insert_spaces(text.replace(' ',''), find_indices(predicted_labels))
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return fixed_text
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default_text = "T hel ittlegi rlra nthro ughth epa rkc has ing abut terfly."
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demo = gr.Interface(fn=fix_space,
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inputs=gr.Textbox(label="Input Text", value=default_text),
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outputs="text")
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demo.launch() |
