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