File size: 13,745 Bytes
c204f33 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 |
import subprocess
from PIL import Image,ImageOps,ImageDraw,ImageFilter
import json
import os
import time
import io
from mp_utils import get_pixel_cordinate_list,extract_landmark,get_pixel_cordinate,get_normalized_xyz
from glibvision.draw_utils import points_to_box,box_to_xy,plus_point,calculate_distance
import numpy as np
from glibvision.pil_utils import fill_points,create_color_image,draw_box
import glibvision.pil_utils
from gradio_utils import save_image,save_buffer,clear_old_files ,read_file
import math
import mp_triangles
from glibvision.cv2_utils import create_color_image as cv2_create_color_image,copy_image,pil_to_bgr_image
import cv2
#TODO move to CV2
# i'm not sure this is fast
def apply_affine_transformation_to_triangle_add(src_tri, dst_tri, src_img, dst_img):
src_tri_np = np.float32(src_tri)
dst_tri_np = np.float32(dst_tri)
h_dst, w_dst = dst_img.shape[:2]
M = cv2.getAffineTransform(src_tri_np, dst_tri_np)
dst_mask = np.zeros((h_dst, w_dst), dtype=np.uint8)
cv2.fillPoly(dst_mask, [np.int32(dst_tri)], 255)
transformed = cv2.warpAffine(src_img, M, (w_dst, h_dst))
transformed = transformed * (dst_mask[:, :, np.newaxis] / 255).astype(np.uint8)
dst_background = dst_img * (1 - (dst_mask[:, :, np.newaxis] / 255)).astype(np.uint8)
dst_img = transformed + dst_background
return dst_img
def apply_affine_transformation_to_triangle_add(src_tri, dst_tri, src_img, dst_img):
src_tri_np = np.float32(src_tri)
dst_tri_np = np.float32(dst_tri)
assert src_tri_np.shape == (3, 2), f"src_tri_np の形状が不正 {src_tri_np.shape}"
assert dst_tri_np.shape == (3, 2), f"dst_tri_np の形状が不正 {dst_tri_np.shape}"
# 透視変換行列の計算
M = cv2.getAffineTransform(src_tri_np, dst_tri_np)
# 画像のサイズ
h_src, w_src = src_img.shape[:2]
h_dst, w_dst = dst_img.shape[:2]
# 元画像から三角形領域を切り抜くマスク生成
#src_mask = np.zeros((h_src, w_src), dtype=np.uint8)
#cv2.fillPoly(src_mask, [np.int32(src_tri)], 255)
# Not 元画像の三角形領域のみをマスクで抽出
src_triangle = src_img #cv2.bitwise_and(src_img, src_img, mask=src_mask)
# 変換行列を使って元画像の三角形領域を目標画像のサイズへ変換
transformed = cv2.warpAffine(src_triangle, M, (w_dst, h_dst))
#print(f"dst_img={dst_img.shape}")
#print(f"transformed={transformed.shape}")
# 変換後のマスクの生成
dst_mask = np.zeros((h_dst, w_dst), dtype=np.uint8)
cv2.fillPoly(dst_mask, [np.int32(dst_tri)], 255)
transformed = cv2.bitwise_and(transformed, transformed, mask=dst_mask)
# 目標画像のマスク領域をクリアするためにデストのインバートマスクを作成
dst_mask_inv = cv2.bitwise_not(dst_mask)
# 目標画像のマスク部分をクリア
dst_background = cv2.bitwise_and(dst_img, dst_img, mask=dst_mask_inv)
# 変換された元画像の三角形部分と目標画像の背景部分を合成
dst_img = cv2.add(dst_background, transformed)
return dst_img
# TODO move PIL
def process_create_webp(images,duration=100, loop=0,quality=85):
frames = []
for image_file in images:
frames.append(image_file)
output_buffer = io.BytesIO()
frames[0].save(output_buffer,
save_all=True,
append_images=frames[1:],
duration=duration,
loop=loop,
format='WebP',
quality=quality
)
return output_buffer.getvalue()
# TODO move numpy
def rotate_point_euler(point, angles,order="xyz"):
"""
オイラー角を使って3Dポイントを回転させる関数
Args:
point: 回転させる3Dポイント (x, y, z)
angles: 各軸周りの回転角度 (rx, ry, rz) [ラジアン]
Returns:
回転後の3Dポイント (x', y', z')
"""
rx, ry, rz = angles
point = np.array(point)
# X軸周りの回転
Rx = np.array([
[1, 0, 0],
[0, np.cos(rx), -np.sin(rx)],
[0, np.sin(rx), np.cos(rx)]
])
# Y軸周りの回転
Ry = np.array([
[np.cos(ry), 0, np.sin(ry)],
[0, 1, 0],
[-np.sin(ry), 0, np.cos(ry)]
])
# Z軸周りの回転
Rz = np.array([
[np.cos(rz), -np.sin(rz), 0],
[np.sin(rz), np.cos(rz), 0],
[0, 0, 1]
])
# 回転行列の合成 (Z軸 -> Y軸 -> X軸 の順で回転)
order = order.lower()
if order == "xyz":
R = Rx @ Ry @ Rz
elif order == "xzy":
R = Rx @ Rz @ Ry
elif order == "yxz":
R = Ry @ Rx @ Rz
elif order == "yzx":
R = Ry @ Rz @ Rx
elif order == "zxy":
R = Rz @ Rx @ Ry
else:
R = Rz @ Ry @ Rx
# 回転後のポイントを計算
rotated_point = R @ point
return rotated_point
def process_face_mesh_spinning(image,draw_type,center_scaleup,animation_direction,z_multiply=0.8,inner_eyes=False,inner_mouth=False):
animation = True
offset_x = 0
offset_y = 0
# use when center_scaleup is True,scale is 0.45(half-size:0.5-margin/ nosetip-to-top or nosetip-to-bottom
scale_up = 1.0
face_landmarker_result = None
if image == None:#app stop support none image,if mode still image,make problem
# Box for no Image Case
image_width = 512
image_height = 512
#image = create_color_image(image_width,image_height,(0,0,0))
points = [(-0.25,-0.25,0),(0.25,-0.25,0),
(0.25,0.25,0),(-0.25,0.25,0)
]
normalized_center_point = [0.5,0.5]
else:
image_width = image.width
image_height = image.height
mp_image,face_landmarker_result = extract_landmark(image,"face_landmarker.task",0,0,True)
def rotate_image():
return None,face_landmarker_result,None
#return rotate_image()
# cordinate eyes
# cordinate all
landmark_points = [get_normalized_xyz(face_landmarker_result.face_landmarks,i) for i in range(0,468)]
# do centering
normalized_center_point = landmark_points[4]
normalized_top_point = landmark_points[10]
normalized_bottom_point = landmark_points[152]
offset_x = normalized_center_point[0]
offset_y = normalized_center_point[1]
offset_z = normalized_center_point[2]
#need aspect?
points = [[point[0]-offset_x,point[1]-offset_y,point[2]*z_multiply] for point in landmark_points]
# split xy-cordinate and z-depth
def split_points_xy_z(points,width,height,center_x,center_y):
xys = []
zs = []
for point in points:
xys.append(
[
point[0]*width*scale_up+center_x,
point[1]*height*scale_up+center_y
]
)
zs.append(point[2])
return xys,zs
def draw_grid_in_center(draw,cx,cy,grid_size,grid_color,width=1,draw_horizontal=True,draw_vertical=True):
w = image.width
h = image.height
x_minus_divide = cx//grid_size
x_plus_divide = (w -cx)//grid_size
y_minus_divide = cy//grid_size
y_plus_divide = (h -cx)//grid_size
for i in range(-x_minus_divide,x_plus_divide+1):
draw.line([(cx+i*grid_size,0),(cx+i*grid_size,h)],fill=grid_color,width=width)
for i in range(-y_minus_divide,y_plus_divide+1):
draw.line([(0,cy+i*grid_size),(w,cy+i*grid_size)],fill=grid_color,width=width)
def draw_grid(image,cx=512,cy=512,first_color=(255,0,0)):
w = image.width
h = image.height
second_grid_size=100
second_color = (128,128,128)
draw = ImageDraw.Draw(image)
draw_grid_in_center(draw,cx,cy,20,(100,100,100))
draw_grid_in_center(draw,cx,cy,100,(192,192,192))
draw.line([(cx,0),(cx,image.height)],fill=first_color)
draw.line([(0,cy),(image.width,cy)],fill=first_color)
def create_triangle_image(points,width,height,center_x,center_y,line_color=(255,255,255),fill_color=None):
cordinates,angled_depth = split_points_xy_z(points,width,height,center_x,center_y)
img = create_color_image(width,height,(0,0,0))
draw = ImageDraw.Draw(img)
triangles = mp_triangles.get_triangles_copy(True,inner_eyes,inner_eyes,inner_mouth)
triangles.sort(key=lambda triangle: sum(angled_depth[index] for index in triangle) / len(triangle)
,reverse=True)
for triangle in triangles:
triangle_cordinates = [cordinates[index] for index in triangle]
glibvision.pil_utils.image_draw_points(draw,triangle_cordinates,line_color,fill_color)
return img
def create_texture_image(image,origin_points,angled_points,width,height,center_x,center_y,line_color=(255,255,255),fill_color=None):
cv2_image = pil_to_bgr_image(image)
#print(f"shape={cv2_image.shape}")
#cv2.imwrite("tmp.jpg",cv2_image)
original_cordinates = []
cordinates,angled_depth = split_points_xy_z(angled_points,width,height,center_x,center_y)
# original point need offset
for point in origin_points:
original_cordinates.append(
[
(point[0]+offset_x)*width,
(point[1]+offset_y)*height
]
)
if cv2_image.shape[2]==3:
cv2_bg_img = cv2_create_color_image(cv2_image,(0,0,0))
else:
cv2_bg_img = cv2_create_color_image(cv2_image,(0,0,0,0))
triangles = mp_triangles.get_triangles_copy(True,inner_eyes,inner_eyes,inner_mouth)
triangles.sort(key=lambda triangle: sum(angled_depth[index] for index in triangle) / len(triangle)
,reverse=True)
for triangle in triangles:
triangle_cordinates = [cordinates[index] for index in triangle]
origin_triangle_cordinates = [original_cordinates[index] for index in triangle]
cv2_bg_img=apply_affine_transformation_to_triangle_add(origin_triangle_cordinates,triangle_cordinates,cv2_image,cv2_bg_img)
img= Image.fromarray(cv2.cvtColor(cv2_bg_img, cv2.COLOR_RGBA2BGRA))
return img
def create_point_image(points,width,height,center_x,center_y):
cordinates,_ = split_points_xy_z(points,width,height,center_x,center_y)
img = create_color_image(width,height,(0,0,0))
glibvision.pil_utils.draw_points(img,cordinates,None,None,3,(255,0,0),3)
return img
def angled_points(points,angles,order="xyz"):
angled_cordinates = []
for point in points:
rotated_np_point = rotate_point_euler(point,angles,order)
angled_cordinates.append(
[
rotated_np_point[0],
rotated_np_point[1],rotated_np_point[2]
]
)
return angled_cordinates
frames = []
#frames.append(create_point_image(points))
frame_duration=100
start_angle=0
end_angle=360
step_angle=10
if draw_type == "Image":
start_angle=-90
end_angle=90
step_angle=30
if not animation:
start_angle=0
end_angle=0
step_angle=360
if image == None:
draw_type="Dot"
if center_scaleup and image!=None:
top_distance = calculate_distance(normalized_center_point,normalized_top_point)
bottom_distance = calculate_distance(normalized_center_point,normalized_bottom_point)
distance = top_distance if top_distance>bottom_distance else bottom_distance
#small_size = image_width if image_width<image_height else image_height
scale_up = 0.45 / distance #half - margin
if image_height>image_width:
scale_up *= image_width/image_height
#print(scale_up)
face_center_x = int(0.5* image_width)#half
face_center_y = int(0.5* image_height)
else:
scale_up = 1.0
face_center_x = int(normalized_center_point[0]* image_width)
face_center_y = int(normalized_center_point[1]* image_height)
rotated_points = None
if animation:
for i in range(start_angle,end_angle,step_angle):
if animation_direction == "X":
angles = [math.radians(i),0,0]
elif animation_direction == "Y":
angles = [0,math.radians(i),0]
else:
angles = [0,0,math.radians(i)]
if draw_type == "Dot":
frames.append(create_point_image(angled_points(points,angles),image_width,image_height,face_center_x,face_center_y))
elif draw_type == "Line":
frames.append(create_triangle_image(angled_points(points,angles),image_width,image_height,face_center_x,face_center_y))
elif draw_type == "Line+Fill":
frames.append(create_triangle_image(angled_points(points,angles),image_width,image_height,face_center_x,face_center_y,(128,128,128),(200,200,200)))
elif draw_type == "Image":
frame_duration=500
frames.append(create_texture_image(image,points,angled_points(points,angles),image_width,image_height,face_center_x,face_center_y))
webp = process_create_webp(frames,frame_duration)
path = save_buffer(webp)
return path,face_landmarker_result,rotated_points |