Create app.py

app.py

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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)
+