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import gradio as gr
import numpy as np
import cv2
from PIL import Image
MAX_COLORS = 12
def get_high_freq_colors(image):
im = image.getcolors(maxcolors=1024*1024)
sorted_colors = sorted(im, key=lambda x: x[0], reverse=True)
freqs = [c[0] for c in sorted_colors]
mean_freq = sum(freqs) / len(freqs)
high_freq_colors = [c for c in sorted_colors if c[0] > max(2, mean_freq/3)] # Ignore colors that occur very few times (less than 2) or less than half the average frequency
return high_freq_colors
def color_quantization(image, n_colors):
# Get color histogram
hist, _ = np.histogramdd(image.reshape(-1, 3), bins=(256, 256, 256), range=((0, 256), (0, 256), (0, 256)))
# Get most frequent colors
colors = np.argwhere(hist > 0)
colors = colors[np.argsort(hist[colors[:, 0], colors[:, 1], colors[:, 2]])[::-1]]
colors = colors[:n_colors]
# Replace each pixel with the closest color
dists = np.sum((image.reshape(-1, 1, 3) - colors.reshape(1, -1, 3))**2, axis=2)
labels = np.argmin(dists, axis=1)
return colors[labels].reshape((image.shape[0], image.shape[1], 3)).astype(np.uint8)
def create_binary_matrix(img_arr, target_color):
print(target_color)
# Create mask of pixels with target color
mask = np.all(img_arr == target_color, axis=-1)
# Convert mask to binary matrix
binary_matrix = mask.astype(int)
return binary_matrix
def process_sketch(image, binary_matrixes):
high_freq_colors = get_high_freq_colors(image)
how_many_colors = len(high_freq_colors)
im2arr = np.array(image) # im2arr.shape: height x width x channel
im2arr = color_quantization(im2arr, n_colors=how_many_colors)
colors_fixed = []
for color in high_freq_colors[1:]:
r = color[1][0]
g = color[1][1]
b = color[1][2]
binary_matrix = create_binary_matrix(im2arr, (r,g,b))
binary_matrixes.append(binary_matrix)
colors_fixed.append(gr.update(value=f'<div class="color-bg-item" style="background-color: rgb({r},{g},{b})"></div>'))
visibilities = []
colors = []
for n in range(MAX_COLORS):
visibilities.append(gr.update(visible=False))
colors.append(gr.update(value=f'<div class="color-bg-item" style="background-color: black"></div>'))
for n in range(how_many_colors-1):
visibilities[n] = gr.update(visible=True)
colors[n] = colors_fixed[n]
return [gr.update(visible=True), binary_matrixes, *visibilities, *colors]
def process_generation(binary_matrixes, master_prompt, *prompts):
clipped_prompts = prompts[:len(binary_matrixes)]
#Now: master_prompt can be used as the main prompt, and binary_matrixes and clipped_prompts can be used as the masked inputs
pass
css = '''
#color-bg{display:flex;justify-content: center;align-items: center;}
.color-bg-item{width: 100%; height: 32px}
#main_button{width:100%}
'''
def update_css(aspect):
if(aspect=='Square'):
width = 512
height = 512
elif(aspect == 'Horizontal'):
width = 768
height = 512
elif(aspect=='Vertical'):
width = 512
height = 768
return gr.update(value=f"<style>#main-image{{width: {width}px}} .fixed-height{{height: {height}px !important}}</style>")
with gr.Blocks(css=css) as demo:
binary_matrixes = gr.State([])
gr.Markdown('''## Control your Stable Diffusion generation with Sketches
This Space demonstrates MultiDiffusion region-based generation using Stable Diffusion model. To get started, draw your masks and type your prompts. More details in the [project page](https://multidiffusion.github.io).
''')
with gr.Row():
with gr.Box(elem_id="main-image"):
with gr.Row():
image = gr.Image(interactive=True, tool="color-sketch", source="canvas", type="pil")
with gr.Row():
aspect = gr.Radio(["Square", "Horizontal", "Vertical"], value="Square", label="Aspect Ratio")
button_run = gr.Button("I've finished my sketch",elem_id="main_button")
prompts = []
colors = []
color_row = [None] * MAX_COLORS
with gr.Column(visible=False) as post_sketch:
general_prompt = gr.Textbox(label="General Prompt")
for n in range(MAX_COLORS):
with gr.Row(visible=False) as color_row[n]:
with gr.Box(elem_id="color-bg"):
colors.append(gr.HTML('<div class="color-bg-item" style="background-color: black"></div>'))
prompts.append(gr.Textbox(label="Prompt for this color"))
final_run_btn = gr.Button("Generate!")
out_image = gr.Image(label="Result")
gr.Markdown('''
![Examples](https://multidiffusion.github.io/pics/tight.jpg)
''')
css_height = gr.HTML("<style>#main-image{width: 512px} .fixed-height{height: 512px !important}</style>")
aspect.change(update_css, inputs=aspect, outputs=css_height)
button_run.click(process_sketch, inputs=[image, binary_matrixes], outputs=[post_sketch, binary_matrixes, *color_row, *colors])
final_run_btn.click(process_generation, inputs=[binary_matrixes, general_prompt, *prompts], outputs=out_image)
demo.launch()