Create app.py

app.py

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+import streamlit as st
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+import tensorflow_addons as tfa
+import cv2
+import tensorflow_hub as hub
+import tensorflow as tf
+from tensorflow.keras.utils import custom_object_scope
+
+os.environ['TFHUB_MODEL_LOAD_FORMAT'] = 'COMPRESSED'
+
+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 Image.fromarray(tensor)
+
+def load(file_uploader):
+    max_dim = 512
+    image = file_uploader
+    image = tf.image.decode_image(image.read(), channels=3)
+    image = tf.image.convert_image_dtype(image, tf.float32)
+
+    shape = tf.cast(tf.shape(image)[:-1], tf.float32)
+    long_dim = max(shape)
+    scale = max_dim / long_dim
+
+    new_shape = tf.cast(shape * scale, tf.int32)
+
+    image = tf.image.resize(image, (256, 256))  # Resize to a consistent shape (256, 256)
+    image = image[tf.newaxis, :]
+    return image
+    
+st.title("Sketch to Real Image Pix2Pix")
+inp = st.file_uploader("Sketch input")
+style = load('')
+
+if inp is not None:
+    img = load(inp)
+    hub_model = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
+    
+    stylized_image = hub_model(img, img)[0]
+    pred = tensor_to_image(stylized_image)
+    
+    toshow = np.array(img[0].numpy() * 255, dtype=np.uint8)  # Convert to uint8
+    st.image(toshow, caption="Uploaded Image")
+    st.image(pred, caption="Generated Real Face")