Create app.py

app.py

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+from diffusers import StableDiffusionPipeline  # Import the StableDiffusionPipeline class from diffusers
+import torch
+
+# Define the model ID for Stable Diffusion
+model_id = "CompVis/stable-diffusion-v1-4"
+
+# Load the pre-trained model
+pipe = StableDiffusionPipeline.from_pretrained(model_id)
+
+# Move the model to GPU if available, otherwise use CPU
+pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Function to generate images based on text prompts
+def generate_image(prompt, output_path="generated_image.png"):
+    # Generate the image
+    image = pipe(prompt).images[0]
+    
+    # Save the generated image
+    image.save(output_path)
+    print(f"Image saved at: {output_path}")
+
+# Example prompts for image generation
+prompt1 = "A futuristic city skyline at sunset"
+generate_image(prompt1, "image1.png")
+
+prompt2 = "A beautiful landscape from mountains during sunrise"
+generate_image(prompt2, "image2.png")
+
+prompt3 = "A beautiful landscape from mountains during sunset"
+generate_image(prompt3, "image3.png")