IDKiro commited on
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1600949
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  1. app.py +119 -0
  2. requirements.txt +23 -0
  3. style.css +213 -0
app.py ADDED
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+ import base64
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+ from io import BytesIO
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+
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+ import gradio as gr
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+ import PIL.Image
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+ import torch
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+
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+ from diffusers import StableDiffusionPipeline, AutoencoderKL, AutoencoderTiny
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+ from peft import PeftModel
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+
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+ device = "cpu" # Linux & Windows
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+ weight_type = torch.float32 # torch.float16 works as well, but pictures seem to be a bit worse
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+
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+ pipe = StableDiffusionPipeline.from_pretrained("IDKiro/sdxs-512-dreamshaper", torch_dtype=weight_type)
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+ pipe.unet = PeftModel.from_pretrained(pipe.unet, "IDKiro/sdxs-512-dreamshaper-anime")
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+ pipe.to(torch_device=device, torch_dtype=weight_type)
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+
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+ vae_tiny = AutoencoderTiny.from_pretrained("IDKiro/sdxs-512-dreamshaper", subfolder="vae")
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+ vae_tiny.to(device, dtype=weight_type)
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+
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+ vae_large = AutoencoderKL.from_pretrained("IDKiro/sdxs-512-dreamshaper", subfolder="vae_large")
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+ vae_tiny.to(device, dtype=weight_type)
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+
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+ def pil_image_to_data_url(img, format="PNG"):
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+ buffered = BytesIO()
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+ img.save(buffered, format=format)
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+ img_str = base64.b64encode(buffered.getvalue()).decode()
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+ return f"data:image/{format.lower()};base64,{img_str}"
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+
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+
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+ def run(
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+ prompt: str,
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+ device_type="GPU",
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+ vae_type=None,
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+ param_dtype='torch.float16',
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+ ) -> PIL.Image.Image:
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+ if vae_type == "tiny vae":
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+ pipe.vae = vae_tiny
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+ elif vae_type == "large vae":
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+ pipe.vae = vae_large
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+
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+ if device_type == "CPU":
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+ device = "cpu"
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+ param_dtype = 'torch.float32'
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+ else:
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+ device = "cuda"
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+
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+ pipe.to(torch_device=device, torch_dtype=torch.float16 if param_dtype == 'torch.float16' else torch.float32)
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+
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+ result = pipe(
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+ prompt=prompt,
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+ guidance_scale=0.0,
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+ num_inference_steps=1,
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+ output_type="pil",
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+ ).images[0]
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+
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+ result_url = pil_image_to_data_url(result)
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+
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+ return (result, result_url)
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+
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+
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+ examples = [
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+ "A photo of beautiful mountain with realistic sunset and blue lake, highly detailed, masterpiece",
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+ ]
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+
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+ with gr.Blocks(css="style.css") as demo:
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+ gr.Markdown("# SDXS-512-DreamShaper (only CPU now)")
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+ with gr.Group():
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+ with gr.Row():
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+ with gr.Column(min_width=685):
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+ with gr.Row():
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+ prompt = gr.Text(
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+ label="Prompt",
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+ show_label=False,
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+ max_lines=1,
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+ placeholder="Enter your prompt",
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+ container=False,
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+ )
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+ run_button = gr.Button("Run", scale=0)
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+
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+ device_choices = ['GPU','CPU']
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+ device_type = gr.Radio(device_choices, label='Device',
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+ value=device_choices[0],
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+ interactive=True,
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+ info='Only CPU now.')
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+
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+ vae_choices = ['tiny vae','large vae']
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+ vae_type = gr.Radio(vae_choices, label='Image Decoder Type',
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+ value=vae_choices[0],
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+ interactive=True,
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+ info='To save GPU memory, use tiny vae. For better quality, use large vae.')
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+
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+ dtype_choices = ['torch.float16','torch.float32']
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+ param_dtype = gr.Radio(dtype_choices,label='torch.weight_type',
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+ value=dtype_choices[0],
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+ interactive=True,
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+ info='To save GPU memory, use torch.float16. For better quality, use torch.float32.')
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+
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+ download_output = gr.Button("Download output", elem_id="download_output")
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+
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+ with gr.Column(min_width=512):
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+ result = gr.Image(label="Result", height=512, width=512, elem_id="output_image", show_label=False, show_download_button=True)
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+
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+ gr.Examples(
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+ examples=examples,
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+ inputs=prompt,
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+ outputs=result,
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+ fn=run
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+ )
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+
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+ demo.load(None,None,None)
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+
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+ inputs = [prompt, device_type, vae_type, param_dtype]
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+ outputs = [result, download_output]
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+ prompt.submit(fn=run, inputs=inputs, outputs=outputs)
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+ run_button.click(fn=run, inputs=inputs, outputs=outputs)
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+
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+ if __name__ == "__main__":
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+ demo.queue().launch(debug=True)
requirements.txt ADDED
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+ einops>=0.6.1
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+ numpy>=1.24.4
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+ opencv-python==4.6.0.66
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+ pillow>=9.5.0
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+ scipy==1.11.1
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+ timm>=0.9.2
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+ tokenizers
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+ torch>=2.0.1
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+ torchaudio>=2.0.2
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+ torchdata==0.6.1
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+ torchvision>=0.15.2
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+ tqdm>=4.65.0
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+ transformers
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+ triton==2.0.0
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+ urllib3<1.27,>=1.25.4
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+ xformers>=0.0.20
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+ accelerate
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+ streamlit-keyup==0.2.0
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+ peft
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+ dominate
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+ diffusers==0.25.1
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+ gradio==3.43.1
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+ hf_transfer
style.css ADDED
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+ @import url('https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.1/css/all.min.css');
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+
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+ /* the outermost contrained of the app */
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+ .main{
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+ display: flex;
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+ justify-content: center;
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+ align-items: center;
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+ width: 1200px;
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+ }
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+
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+ /* #main_row{
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+
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+ } */
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+
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+ /* hide this class */
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+ .svelte-p4aq0j {
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+ display: none;
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+ }
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+
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+ .wrap.svelte-p4aq0j.svelte-p4aq0j {
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+ display: none;
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+ }
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+
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+ #download_sketch{
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+ display: none;
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+ }
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+
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+ #download_output{
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+ display: none;
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+ }
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+
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+ #column_input, #column_output{
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+ width: 500px;
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+ display: flex;
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+ /* justify-content: center; */
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+ align-items: center;
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+ }
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+
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+ #tools_header, #input_header, #output_header, #process_header {
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+ display: flex;
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+ justify-content: center;
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+ align-items: center;
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+ width: 400px;
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+ }
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+
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+
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+ #nn{
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+ width: 100px;
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+ height: 100px;
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+ }
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+
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+
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+ #column_process{
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+ display: flex;
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+ justify-content: center; /* Center horizontally */
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+ align-items: center; /* Center vertically */
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+ height: 600px;
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+ }
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+
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+ /* this is the "pix2pix-turbo" above the process button */
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+ #description > span{
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+ display: flex;
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+ justify-content: center; /* Center horizontally */
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+ align-items: center; /* Center vertically */
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+ }
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+
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+ /* this is the "UNDO_BUTTON, X_BUTTON" */
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+ div.svelte-1030q2h{
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+ width: 30px;
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+ height: 30px;
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+ display: none;
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+ }
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+
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+
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+ #component-5 > div{
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+ border: 0px;
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+ box-shadow: none;
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+ }
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+
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+ #cb-eraser, #cb-line{
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+ display: none;
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+ }
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+
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+ /* eraser text */
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+ #cb-eraser > label > span{
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+ display: none;
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+ }
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+ #cb-line > label > span{
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+ display: none;
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+ }
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+
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+
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+ .button-row {
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+ display: flex;
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+ justify-content: center;
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+ align-items: center;
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+ height: 50px;
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+ border: 0px;
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+ }
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+
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+ #my-toggle-pencil{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/pencil.svg");
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+ background-color: white;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+ }
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+
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+ #my-toggle-pencil.clicked{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/pencil-fill.svg");
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+ transform: scale(0.98);
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+ background-color: gray;
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+ background-size: cover;
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+ /* background-size: 95%;
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+ background-position: center; */
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+ /* border: 2px solid #000; */
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+ }
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+
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+
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+ #my-toggle-eraser{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/eraser.svg");
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+ background-color: white;
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+ background-color: white;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+ }
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+
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+ #my-toggle-eraser.clicked{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/eraser-fill.svg");
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+ transform: scale(0.98);
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+ background-color: gray;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+ }
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+
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+
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+
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+ #my-button-undo{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/arrow-counterclockwise.svg");
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+ background-color: white;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+ }
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+
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+ #my-button-clear{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/x-lg.svg");
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+ background-color: white;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+
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+ }
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+
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+
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+ #my-button-down{
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+ background-image: url("https://icons.getbootstrap.com/assets/icons/arrow-down.svg");
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+ background-color: white;
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+ background-size: cover;
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+ margin: 0px;
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+ box-shadow: none;
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+ width: 40px;
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+ height: 40px;
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+
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+ }
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+
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+ .pad2{
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+ padding: 2px;
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+ background-color: white;
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+ border: 2px solid #000;
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+ margin: 10px;
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+ display: flex;
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+ justify-content: center; /* Center horizontally */
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+ align-items: center; /* Center vertically */
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+ }
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+
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+
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+
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+
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+ #output_image, #input_image{
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+ border-radius: 0px;
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+ border: 5px solid #000;
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+ border-width: none;
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+ }
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+
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+
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+ #output_image > img{
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+ border: 5px solid #000;
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+ border-radius: 0px;
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+ border-width: none;
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+ }
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+
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+ #input_image > div.image-container.svelte-p3y7hu > div.wrap.svelte-yigbas > canvas:nth-child(1){
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+ border: 5px solid #000;
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+ border-radius: 0px;
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+ border-width: none;
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+ }