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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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description = ( |
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"SpaceGen is an academic project developed by Asaf Delmedigo and Romi Zarchi " |
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"during their graduate studies in Neuroscience and Data Science.\n" |
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"It demonstrates the use of an LSTM neural network for automatic detection " |
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"and correction of missing spaces in text.\n" |
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"Currently, the model supports English text only.\n" |
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"Feedback is welcome at: [email protected]" |
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) |
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demo = gr.Interface( |
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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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title="SpaceGen – Text Space Correction with LSTM", |
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description=description |
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) |
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demo.launch() |
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