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import gradio as gr | |
import torch | |
from diffusers import KandinskyPriorPipeline, KandinskyPipeline | |
import qrcode | |
IMAGE_WIDTH = 512 | |
IMAGE_HEIGHT = 512 | |
device = 0 | |
if not torch.cuda.is_available(): | |
print("GPU isn't available. Running on CPU.") | |
device = -1 | |
pipe_prior = KandinskyPriorPipeline.from_pretrained( | |
"kandinsky-community/kandinsky-2-1-prior", torch_dtype=torch.float16 | |
) | |
pipe_prior.to("cuda") | |
pipe = KandinskyPipeline.from_pretrained( | |
"kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16) | |
pipe.to("cuda") | |
def interpolate_image(qr_code_value, image, qr_image_weight, images_weight): | |
qr_code = qrcode.make(qr_code_value).resize((IMAGE_WIDTH, IMAGE_HEIGHT)) | |
image_texts = [image, qr_code] | |
weights = [images_weight, qr_image_weight] | |
prompt = "" | |
prior_out = pipe_prior.interpolate(image_texts, weights) | |
result = pipe(prompt, **prior_out, height=IMAGE_HEIGHT, width=IMAGE_WIDTH) | |
return result.images | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
qr_input = gr.Text(label="QR Code Value") | |
image = gr.Image(label="Images", type="pil") | |
with gr.Row(): | |
qr_image_weight = gr.Slider( | |
label="QR Image Weight", value=0.5, maximum=1) | |
images_weight = gr.Slider( | |
label="Input Images Weight", value=0.3, maximum=1) | |
submit_button = gr.Button("Submit") | |
with gr.Column(): | |
output = gr.Gallery(label="Output") | |
output.style(grid=4) | |
submit_button.click( | |
fn=interpolate_image, inputs=[ | |
qr_input, image, qr_image_weight, images_weight], outputs=output, api_name="interpolate" | |
) | |
gr.Examples( | |
examples=[["http://huggingface.co", "Starry_Night.jpg"]], | |
inputs=[qr_input, image], | |
outputs=output | |
) | |
demo.theme = gr.themes.Base() | |
demo.launch() | |