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import gradio as gr |
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from tensorflow.keras.models import model_from_json |
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import numpy as np |
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def predict_age_gender(image): |
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json_file = open('final_mobilenet.json', 'r') |
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loaded_file_json = json_file.read() |
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json_file.close() |
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model = model_from_json(loaded_file_json) |
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model.load_weights('final_mobilenet.h5') |
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img_pixels = np.expand_dims(image, axis=0) |
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img_pixels = image.astype('float') |
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img_pixels = img_pixels.reshape((1, 128, 128, 3)) |
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img_pixels /= 255 |
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predict = model.predict(img_pixels) |
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gender_predict = predict[0] |
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age_predict = predict[1] |
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return {'Gender': ['Fmale' if gender_predict > 0.5 else 'Male'], 'Age': age_predict[0][0]} |
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iface = gr.Interface(predict_age_gender, gr.Image(), gr.Text()) |
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iface.launch(share=True) |
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