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()