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Browse files- .gitignore +13 -0
- README.md +2 -8
- index.py +92 -0
- requirements.txt +2 -0
.gitignore
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.vercel
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*.log
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*.pyc
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__pycache__
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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README.md
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---
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title:
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colorFrom: yellow
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colorTo: gray
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sdk: gradio
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sdk_version: 4.36.1
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: repeating-pattern-generator
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app_file: index.py
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sdk: gradio
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sdk_version: 4.36.1
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---
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index.py
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import os
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import base64
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import numpy as np
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from PIL import Image, ImageChops, ImageDraw
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import io
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import requests
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import replicate
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import gradio as gr
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from dotenv import load_dotenv, find_dotenv
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# Locate the .env file
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dotenv_path = find_dotenv()
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load_dotenv(dotenv_path)
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REPLICATE_API_TOKEN = os.getenv('REPLICATE_API_TOKEN')
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def generate_pattern(image, prompt):
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# Convert the numpy array to a PIL image
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starter_image_pil = Image.fromarray(image.astype('uint8'))
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# Resize the starter image if either dimension is larger than 768 pixels
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if starter_image_pil.size[0] > 768 or starter_image_pil.size[1] > 768:
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# Calculate the new size while maintaining the aspect ratio
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if starter_image_pil.size[0] > starter_image_pil.size[1]:
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# Width is larger than height
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new_width = 768
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new_height = int((768 / starter_image_pil.size[0]) * starter_image_pil.size[1])
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else:
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# Height is larger than width
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new_height = 768
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new_width = int((768 / starter_image_pil.size[1]) * starter_image_pil.size[0])
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# Resize the image
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starter_image_pil = starter_image_pil.resize((new_width, new_height), Image.LANCZOS)
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# Move the image horizontally and vertically by 50%
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width, height = starter_image_pil.size
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horizontal_shift = width // 2
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vertical_shift = height // 2
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transformed_image_pil = ImageChops.offset(starter_image_pil, horizontal_shift, vertical_shift)
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# Create a new image with black background and white cross
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cross_image_pil = Image.new('RGB', (width, height), 'black')
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draw = ImageDraw.Draw(cross_image_pil)
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line_width = 50
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# Draw vertical line
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draw.rectangle([(width // 2 - line_width // 2, 0), (width // 2 + line_width // 2, height)], fill='white')
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# Draw horizontal line
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draw.rectangle([(0, height // 2 - line_width // 2), (width, height // 2 + line_width // 2)], fill='white')
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buffered = io.BytesIO()
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transformed_image_pil.save(buffered, format="JPEG")
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image_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
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buffered = io.BytesIO()
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cross_image_pil.save(buffered, format="JPEG")
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cross_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
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input = {
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"prompt": prompt + " smooth background",
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"negative_prompt": "worst quality, low quality, cartoons, sketch, ugly, lowres",
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"image": "data:image/jpeg;base64," + image_base64,
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"mask": "data:image/jpeg;base64," + cross_base64,
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"num_inference_steps": 25,
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"num_outputs": 3,
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}
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output = replicate.run(
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"lucataco/sdxl-inpainting:a5b13068cc81a89a4fbeefeccc774869fcb34df4dbc92c1555e0f2771d49dde7",
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input=input
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)
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images = []
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for i in range(min(len(output), 3)):
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image_url = output[i]
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response = requests.get(image_url)
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images.append(Image.open(io.BytesIO(response.content)))
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# Add empty images if fewer than 3 were returned
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while len(images) < 3:
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images.append(Image.new('RGB', (width, height), 'gray'))
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return images
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demo = gr.Interface(fn=generate_pattern, inputs=["image", "text"], outputs=["image", "image", "image"])
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demo.launch(share=False)
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requirements.txt
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gradio
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replicate
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