Create app.py

app.py

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+import os
+import tensorflow as tf
+os.environ['TFHUB_MODEL_LOAD_FORMAT'] = 'COMPRESSED'
+import numpy as np
+import PIL.Image
+import gradio as gr
+import tensorflow_hub as hub
+import matplotlib.pyplot as plt
+
+hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
+
+def tensor_to_image(tensor):
+    tensor = tensor*255
+    tensor = np.array(tensor, dtype=np.uint8)
+    if np.ndim(tensor) > 3:
+        assert tensor.shape[0] == 1
+        tensor = tensor[0]
+    return PIL.Image.fromarray(tensor)
+
+content_image_input = gr.Image(label="Content Image")
+style_image_input = gr.Image(label="Style Image")
+
+text = "#Developer: Aditya Jadhav   #College: Government Polytechnic Nagpur   #Branch: AIML (Artificial Intelligence and Machine Learning), 3rd year   #Date: 17th November 2023   #LinkedIn: Aditya Jadhav's LinkedIn   #GitHub: Aditya Jadhav's GitHub"
+my_list = text.split("\n")
+my_string = "\n".join(my_list)
+
+text2 = "The application focuses on neural style transfer, where the style from a style image is applied to a content image."
+
+def perform_neural_transfer(content_image_input, style_image_input):
+    # Load content images
+    content_image = content_image_input.astype(np.float32)[np.newaxis, ...] / 255.
+    style_image = style_image_input.astype(np.float32)[np.newaxis, ...] / 255.
+
+    # Apply neural style transfer
+    outputs = hub_module(tf.constant(content_image), tf.constant(style_image))
+    stylized_image = outputs[0]
+
+    return tensor_to_image(stylized_image)
+
+
+app_interface = gr.Interface(
+    fn=perform_neural_transfer,
+    inputs=[content_image_input, style_image_input],
+    outputs="image",
+    title="Art Generation with Neural Style Transfer",
+    article=my_string,
+    description=text2,
+    theme = 'Default',
+    concurrency_limit =2,
+    examples=[
+        ['content1.jpg','image1.jpg'],
+            [None,'image2.jpg'],
+            [None,'image4.jpg'],
+        [None,'image5.jpg'],
+        [None,'image6.jpg'],
+        ]
+)
+
+app_interface.launch(debug =True)