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try: |
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import tensorflow as tf |
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print("TensorFlow version:", tf.__version__) |
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except ImportError: |
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print("TensorFlow is not installed. Installing now...") |
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try: |
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import pip |
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pip.main(['install', 'tensorflow']) |
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except AttributeError: |
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import subprocess |
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subprocess.call(['pip', 'install', 'tensorflow']) |
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|
|
|
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try: |
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import tensorflow as tf |
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print("TensorFlow has been successfully installed. Version:", tf.__version__) |
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except ImportError: |
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print("Installation failed. Please install TensorFlow manually.") |
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import gradio as gr |
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import numpy as np |
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from tensorflow.keras.models import load_model |
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|
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loaded_model = load_model("gender_classifier_model.h5") |
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def myfun(img): |
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img = tf.image.resize(img, (64, 64)) |
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x = tf.keras.preprocessing.image.img_to_array(img) |
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x = np.expand_dims(x, axis=0) |
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loaded_classes = loaded_model.predict(x, batch_size=1) |
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print(loaded_classes) |
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if loaded_classes[0] > 0.5: |
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return 'Is a Man' |
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else: |
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return 'Is A Woman' |
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|
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|
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iface = gr.Interface(fn=myfun, inputs=gr.Image(label='Drop an Image or Open Camera to Classify'), outputs=gr.Text()) |
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iface.launch() |
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