Create app.py

app.py

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+import io
+import requests
+from PIL import Image
+import torch
+from torchvision import transforms
+from torchvision.utils import save_image
+from torchvision.transforms.functional import resize
+from argparse import Namespace
+
+# Load pre-trained StyleGAN2 model from Hugging Face
+model = torch.hub.load('huggingface/pytorch-pretrained-StyleGAN2', 'StyleGAN2')
+
+# Set device to GPU if available
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+model.to(device)
+
+# Set seed for reproducibility
+torch.manual_seed(0)
+
+# Define function to generate image from text prompt
+def generate_image(prompt):
+    # Convert text prompt to embeddings using StyleGAN2's tokenizer
+    embeddings = model.gen.encode(prompt)
+
+    # Generate image from embeddings
+    with torch.no_grad():
+        generated_image = model.gen.decode(embeddings, input_is_latent=True)
+
+    # Resize and save image
+    generated_image = generated_image.clamp(0, 1)
+    generated_image = resize(generated_image, (256, 256), interpolation=Image.LANCZOS)
+    image_tensor = transforms.ToTensor()(generated_image)
+    image_tensor = image_tensor.unsqueeze(0)
+    save_image(image_tensor, 'output.png')
+
+# Example usage
+generate_image("A peaceful countryside with a lake and mountains in the distance")
+
+# Load generated image and display
+image = Image.open('output.png')
+image.show()