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import cv2
import os
import numpy as np
from skimage.filters import gaussian
from test import evaluate
import streamlit as st
from PIL import Image, ImageColor
def sharpen(img):
img = img * 1.0
gauss_out = gaussian(img, sigma=5, multichannel=True)
alpha = 1.5
img_out = (img - gauss_out) * alpha + img
img_out = img_out / 255.0
mask_1 = img_out < 0
mask_2 = img_out > 1
img_out = img_out * (1 - mask_1)
img_out = img_out * (1 - mask_2) + mask_2
img_out = np.clip(img_out, 0, 1)
img_out = img_out * 255
return np.array(img_out, dtype=np.uint8)
def hair(image, parsing, part=17, color=[230, 50, 20]):
b, g, r = color #[10, 50, 250] # [10, 250, 10]
tar_color = np.zeros_like(image)
tar_color[:, :, 0] = b
tar_color[:, :, 1] = g
tar_color[:, :, 2] = r
np.repeat(parsing[:, :, np.newaxis], 3, axis=2)
image_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
tar_hsv = cv2.cvtColor(tar_color, cv2.COLOR_BGR2HSV)
if part == 12 or part == 13:
image_hsv[:, :, 0:2] = tar_hsv[:, :, 0:2]
else:
image_hsv[:, :, 0:1] = tar_hsv[:, :, 0:1]
changed = cv2.cvtColor(image_hsv, cv2.COLOR_HSV2BGR)
if part == 17:
changed = sharpen(changed)
changed[parsing != part] = image[parsing != part]
return changed
DEMO_IMAGE = 'imgs/116.jpg'
st.title('Virtual Makeup')
st.sidebar.title('Virtual Makeup')
st.sidebar.subheader('Parameters')
table = {
'hair': 17,
'upper_lip': 12,
'lower_lip': 13,
}
img_file_buffer = st.sidebar.file_uploader("Upload an image", type=[ "jpg", "jpeg",'png'])
if img_file_buffer is not None:
image = np.array(Image.open(img_file_buffer))
demo_image = img_file_buffer
else:
demo_image = DEMO_IMAGE
image = np.array(Image.open(demo_image))
#st.set_option('deprecation.showfileUploaderEncoding', False)
new_image = image.copy()
st.subheader('Original Image')
st.image(image,use_column_width = True)
cp = 'cp/79999_iter.pth'
ori = image.copy()
h,w,_ = ori.shape
#print(h)
#print(w)
image = cv2.resize(image,(1024,1024))
parsing = evaluate(demo_image, cp)
parsing = cv2.resize(parsing, image.shape[0:2], interpolation=cv2.INTER_NEAREST)
parts = [table['hair'], table['upper_lip'], table['lower_lip']]
hair_color = st.sidebar.color_picker('Pick the Hair Color', '#000')
hair_color = ImageColor.getcolor(hair_color, "RGB")
lip_color = st.sidebar.color_picker('Pick the Lip Color', '#edbad1')
lip_color = ImageColor.getcolor(lip_color, "RGB")
colors = [hair_color, lip_color, lip_color]
for part, color in zip(parts, colors):
image = hair(image, parsing, part, color)
image = cv2.resize(image,(w,h))
st.subheader('Output Image')
st.image(image,use_column_width = True)
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