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Update app.py
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app.py
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@@ -1,63 +1,63 @@
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import os
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from dotenv import load_dotenv
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import torch
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from torch import autocast
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from diffusers import StableDiffusionPipeline
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import gradio as gr # Import Gradio
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from PIL import Image
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# Load the environment variables from .env
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load_dotenv()
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class StableBuddyApp:
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def __init__(self):
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# Set up the Stable Diffusion pipeline
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model_id = "CompVis/stable-diffusion-v1-4"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Get the auth_token from the environment variable
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auth_token = os.getenv("AUTH_TOKEN")
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if not auth_token:
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raise ValueError("AUTH_TOKEN environment variable is not set.")
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# Use float16 and fp16 so that stable diffusion can work on 4GB VRAM
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self.pipe = StableDiffusionPipeline.from_pretrained(
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model_id, revision='fp16', torch_dtype=torch.float16, use_auth_token=auth_token
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)
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self.pipe.to(device)
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def generate_image(self, prompt):
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"""Generate an image based on the prompt."""
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try:
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with autocast(
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image = self.pipe(prompt, guidance_scale=8.5).images[0]
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# Save the generated image temporarily
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image_path = 'data/generated_image.png'
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image.save(image_path)
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return image_path # Return the image path for Gradio to display
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except Exception as e:
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print(f"An error occurred: {e}")
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return None # In case of an error, return None
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# Create an instance of the StableBuddyApp
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stable_buddy_app = StableBuddyApp()
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# Create Gradio Interface with separate buttons
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def generate_and_download(prompt):
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image_path = stable_buddy_app.generate_image(prompt)
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return image_path, image_path # Return image for display and for download link
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# Create Gradio Interface
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iface = gr.Interface(
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fn=generate_and_download, # Function to call
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inputs=gr.Textbox(label="Enter Prompt"), # Text input for the prompt
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outputs=[gr.Image(type="filepath", label="Generated Image"), gr.File(label="Download Image")], # Two outputs for display and download
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title="Stable Buddy",
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description="Generate images using Stable Diffusion."
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)
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# Launch the Gradio app
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iface.launch()
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import os
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from dotenv import load_dotenv
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import torch
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from torch import autocast
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from diffusers import StableDiffusionPipeline
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import gradio as gr # Import Gradio
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from PIL import Image
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# Load the environment variables from .env
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load_dotenv()
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class StableBuddyApp:
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def __init__(self):
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# Set up the Stable Diffusion pipeline
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model_id = "CompVis/stable-diffusion-v1-4"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Get the auth_token from the environment variable
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auth_token = os.getenv("AUTH_TOKEN")
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if not auth_token:
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raise ValueError("AUTH_TOKEN environment variable is not set.")
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# Use float16 and fp16 so that stable diffusion can work on 4GB VRAM
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self.pipe = StableDiffusionPipeline.from_pretrained(
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model_id, revision='fp16', torch_dtype=torch.float16, use_auth_token=auth_token
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)
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self.pipe.to(device)
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def generate_image(self, prompt):
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"""Generate an image based on the prompt."""
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try:
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with autocast(device):
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image = self.pipe(prompt, guidance_scale=8.5).images[0]
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# Save the generated image temporarily
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image_path = 'data/generated_image.png'
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image.save(image_path)
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return image_path # Return the image path for Gradio to display
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except Exception as e:
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print(f"An error occurred: {e}")
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return None # In case of an error, return None
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# Create an instance of the StableBuddyApp
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stable_buddy_app = StableBuddyApp()
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# Create Gradio Interface with separate buttons
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def generate_and_download(prompt):
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image_path = stable_buddy_app.generate_image(prompt)
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return image_path, image_path # Return image for display and for download link
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# Create Gradio Interface
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iface = gr.Interface(
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fn=generate_and_download, # Function to call
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inputs=gr.Textbox(label="Enter Prompt"), # Text input for the prompt
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outputs=[gr.Image(type="filepath", label="Generated Image"), gr.File(label="Download Image")], # Two outputs for display and download
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title="Stable Buddy",
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description="Generate images using Stable Diffusion."
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)
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# Launch the Gradio app
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iface.launch()
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