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import gradio as gr | |
import numpy as np | |
def spell_to_image(x, special_text): | |
spell = '' | |
spell += 'Esta imagen es limpiada de energía caotica, dañida y de la mala intención' | |
spell += 'pero mantiene cualquier energía sana de los lugares, seres, objetos y buenas intenciones presentes' | |
spell += 'OM AH HUNG, para limpiar' | |
spell += 'esta imagen es activada magicamente para emanar buena energía' | |
spell += 'reforzamos la buena energía, las buenas intenciones, los buenos deseos, el amor' | |
spell += 'aplicamos la siguiente conjuro: ' + special_text | |
spell += 'OM MANI PADME HUNG'; | |
spell += 'para el beneficio de todos los seres' | |
return x | |
with gr.Blocks() as demo: | |
gr.Markdown("# Radionic App") | |
gr.Markdown( | |
''' This is an experimental project. The goal is to create a digital interface for the clean protection and digital images of subtle energies. The idea is simple, the application applies a subtle program in the form of a spell on the image to modify the subtle vibration of the image. The project is based on radionic machines. | |
### Instructions | |
The process is very simple. Upload an image. Put a wish or intention for the image and apply it with the clean button. | |
Try to feel what happens in the result image. | |
There is some examples you can use. | |
If you know about Radionics, try to add a number rate to be apply to the image and test the result | |
''' | |
) | |
with gr.Row(): | |
with gr.Column(scale=1): | |
image_input = gr.Image() | |
spell_input = gr.Text(lines=2, placeholder="Write your own spell") | |
spell_button = gr.Button("Clean and protect") | |
with gr.Column(scale=2): | |
image_output = gr.Image() | |
spell_button.click(spell_to_image, inputs=[image_input,spell_input], outputs=image_output) | |
examples = gr.Examples(examples=['bernd-dittrich-unsplash.jpg', | |
'leiada-krozjhen-8nP8jsg3u68-unsplash.jpg', | |
'michael-martinelli-cnt3JwRn4eI-unsplash.jpg', | |
'mustafa-aslan-CZLuLLDC8mQ-unsplash.jpg', | |
'quang-nguyen-vinh-3il07gRCne0-unsplash.jpg'], | |
inputs=[image_input]) | |
demo.launch() |