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py-3d-face-reconstruction
Commit c2204dea authored by Richard Torenvliet's avatar Richard Torenvliet
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Moved from the use of python solve, to simply move to use multiplication 

It's now around 3x faster then before
parent cb6d90c9
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Showing with 188 additions and 11311 deletions
makefile
View file @ c2204dea
......@@ -12,7 +12,7 @@ include actions.mk
include src/reconstruction/build.mk
data: data/imm_face_db
reconstruction: texture.so halide src/reconstruction/texture_halide
reconstruction: texture.so src/reconstruction/texture_halide
OS := $(shell uname)
......
src/reconstruction/texture.c deleted 100644 → 0
View file @ cb6d90c9
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src/reconstruction/texture.pyx
View file @ c2204dea
......@@ -2,6 +2,7 @@ cimport cython
import numpy as np
cimport numpy as np
from cpython cimport array as c_array
from cython.view cimport array as cvarray
DTYPE_int = np.int
ctypedef np.int_t DTYPE_int_t
......@@ -11,6 +12,7 @@ DTYPE_float64 = np.float64
ctypedef np.float32_t DTYPE_float32_t
ctypedef np.float64_t DTYPE_float64_t
ctypedef float * float_ptr
cdef inline float cross_product(int v1_x, int v1_y, int v2_x, int v2_y):
......@@ -18,8 +20,7 @@ cdef inline float cross_product(int v1_x, int v1_y, int v2_x, int v2_y):
return (v1_x * v2_y) - (v1_y * v2_x)
cdef inline np.ndarray[double, ndim=1] cartesian2barycentric(
int r1_x, r1_y, int r2_x, int r2_y, int r3_x, int r3_y, int r_x, int r_y):
def cartesian2barycentric_slow_test(int r1_x, r1_y, int r2_x, int r2_y, int r3_x, int r3_y, int r_x, int r_y):
"""
Given a triangle spanned by three cartesion points
r1, r2, r2, and point r, return the barycentric weights l1, l2, l3.
......@@ -39,6 +40,84 @@ cdef inline np.ndarray[double, ndim=1] cartesian2barycentric(
return np.linalg.solve(a, b)
def cartesian2barycentric_test(
float x_1, float y_1, float x_2, float y_2, float x_3, float y_3, float x, float y):
"""
lambda_1 = (y_2 - y_3)(x - x_3) + (x_3 - x_2)(y - y_3) /
(y_2-y_3)(x_1-x_3)+(x_3-x_2)(y_1-y_3)
lambda_2 = (y_3 - y_1)(x - x_3) + (x_1 - x_3)(y - y_3) /
(y_2-y_3)(x_1-x_3)+(x_3-x_2)(y_1-y_3)
lambda_3 = 1 lambda_1 - lambda_2
Returns:
ndarray (of dim 3) weights of the barycentric coordinates
"""
cdef float lambda_1 = ((y_2 - y_3) * (x - x_3) + (x_3 - x_2) * (y - y_3)) / \
((y_2 - y_3) * (x_1 - x_3) + (x_3 - x_2) * (y_1 - y_3))
cdef float lambda_2 = ((y_3 - y_1) * (x - x_3) + (x_1 - x_3) * (y - y_3)) / \
((y_2 - y_3) * (x_1 - x_3) + (x_3 - x_2) * (y_1 - y_3))
cdef float lambda_3 = 1 - lambda_1 - lambda_2
return [lambda_1, lambda_2, lambda_3]
cdef inline cartesian2barycentric(
float x_1, float y_1, float x_2, float y_2, float x_3, float y_3, float
x, float y, float[:] lambdas):
"""
lambda_1 = (y_2 - y_3)(x - x_3) + (x_3 - x_2)(y - y_3) /
(y_2-y_3)(x_1-x_3)+(x_3-x_2)(y_1-y_3)
lambda_2 = (y_3 - y_1)(x - x_3) + (x_1 - x_3)(y - y_3) /
(y_2-y_3)(x_1-x_3)+(x_3-x_2)(y_1-y_3)
lambda_3 = 1 lambda_1 - lambda_2
Returns:
ndarray (of dim 3) weights of the barycentric coordinates
"""
lambdas[0] = ((y_2 - y_3) * (x - x_3) + (x_3 - x_2) * (y - y_3)) / \
((y_2 - y_3) * (x_1 - x_3) + (x_3 - x_2) * (y_1 - y_3))
lambdas[1] = ((y_3 - y_1) * (x - x_3) + (x_1 - x_3) * (y - y_3)) / \
((y_2 - y_3) * (x_1 - x_3) + (x_3 - x_2) * (y_1 - y_3))
#cdef float lambda_3 = 1 - lambda_1 - lambda_2
#a = np.array([
# [r1_x, r2_x, r3_x],
# [r1_y, r2_y, r3_y],
# [1, 1, 1]
#])
#b = np.array([r_x, r_y, 1])
#return np.linalg.solve(a, b)
cdef inline np.ndarray[double, ndim=1] cartesian2barycentric_slow(
int r1_x, r1_y, int r2_x, int r2_y, int r3_x, int r3_y, int
r_x, int r_y):
"""
Given a triangle spanned by three cartesion points
r1, r2, r2, and point r, return the barycentric weights l1, l2, l3.
Returns:
ndarray (of dim 3) weights of the barycentric coordinates
"""
a = np.array([
[r1_x, r2_x, r3_x],
[r1_y, r2_y, r3_y],
[1, 1, 1]
])
b = np.array([r_x, r_y, 1])
return np.linalg.solve(a, b)
cdef inline np.ndarray[double, ndim=2] barycentric2cartesian(
int x1, int x2, int x3, int y1, int y2, int y3,
......@@ -75,18 +154,17 @@ def fill_triangle(np.ndarray[unsigned char, ndim=3] src,
cdef np.ndarray matrix = np.full([3, 3], fill_value=1, dtype=DTYPE_int)
cdef np.ndarray src_loc = np.zeros([3, 1], dtype=DTYPE_float64)
cdef np.ndarray dst_loc = np.zeros([3, 1], dtype=DTYPE_float64)
cdef int w = x_max - x_min
cdef int h = y_max - y_min
cdef int new_offset
#cdef np.ndarray src_reshaped = src[offset:offset + (w * h * 3)].reshape((h, w, 3))
cdef c_array.array dst_loc = c_array.array('f', [0., 0.])
for j, y in enumerate(xrange(y_min, y_max)):
for i, x in enumerate(xrange(x_min, x_max)):
dst_loc = cartesian2barycentric(
x1, y1, x2, y2, x3, y3, x, y
cartesian2barycentric(
x1, y1, x2, y2, x3, y3, x, y, dst_loc
)
s = dst_loc[0]
......@@ -98,53 +176,53 @@ def fill_triangle(np.ndarray[unsigned char, ndim=3] src,
dst[y, x, :] = src[y, x, :]
@cython.boundscheck(False)
@cython.wraparound(False)
def fill_triangle_src_dst(np.ndarray[unsigned char, ndim=3] src,
np.ndarray[unsigned char, ndim=3] dst,
int src_x1, int src_y1, int src_x2, int src_y2,
int src_x3, int src_y3,
int dst_x1, int dst_y1, int dst_x2, int dst_y2,
int dst_x3, int dst_y3,
int offset_x, int offset_y):
cdef np.ndarray triangle_x = np.array([dst_x1, dst_x2, dst_x3])
cdef np.ndarray triangle_y = np.array([dst_y1, dst_y2, dst_y3])
cdef int x_min = np.argmin(triangle_x)
cdef int x_max = np.argmax(triangle_x)
cdef int y_min = np.argmin(triangle_y)
cdef int y_max = np.argmax(triangle_y)
cdef np.ndarray L = np.zeros([3, 1], dtype=DTYPE_float32)
cdef np.ndarray matrix = np.full([3, 3], fill_value=1, dtype=DTYPE_int)
cdef np.ndarray src_loc = np.zeros([3, 1], dtype=DTYPE_float64)
cdef np.ndarray dst_loc = np.zeros([3, 1], dtype=DTYPE_float64)
for j, y in enumerate(xrange(triangle_y[y_min], triangle_y[y_max])):
for i, x in enumerate(xrange(triangle_x[x_min], triangle_x[x_max])):
dst_loc = cartesian2barycentric(
dst_x1, dst_y1, dst_x2, dst_y2, dst_x3, dst_y3, x, y
)
s = dst_loc[0]
t = dst_loc[1]
if s >= -0.001 and t >= -0.001 and s + t <= 1.001:
L[0] = s
L[1] = t
L[2] = 1 - s - t
src_loc = barycentric2cartesian(
src_x1, src_x2, src_x3,
src_y1, src_y2, src_y3,
matrix,
L
)
dst[y, x, :] = src[src_loc[1][0], src_loc[0][0], :]
#@cython.boundscheck(False)
#@cython.wraparound(False)
#def fill_triangle_src_dst(np.ndarray[unsigned char, ndim=3] src,
# np.ndarray[unsigned char, ndim=3] dst,
# int src_x1, int src_y1, int src_x2, int src_y2,
# int src_x3, int src_y3,
# int dst_x1, int dst_y1, int dst_x2, int dst_y2,
# int dst_x3, int dst_y3,
# int offset_x, int offset_y):
#
# cdef np.ndarray triangle_x = np.array([dst_x1, dst_x2, dst_x3])
# cdef np.ndarray triangle_y = np.array([dst_y1, dst_y2, dst_y3])
#
# cdef int x_min = np.argmin(triangle_x)
# cdef int x_max = np.argmax(triangle_x)
# cdef int y_min = np.argmin(triangle_y)
# cdef int y_max = np.argmax(triangle_y)
#
# cdef np.ndarray L = np.zeros([3, 1], dtype=DTYPE_float32)
# cdef np.ndarray matrix = np.full([3, 3], fill_value=1, dtype=DTYPE_int)
#
# cdef np.ndarray src_loc = np.zeros([3, 1], dtype=DTYPE_float64)
# cdef c_array.array dst_loc = c_array.array('f', [0., 0.])
#
# for j, y in enumerate(xrange(triangle_y[y_min], triangle_y[y_max])):
# for i, x in enumerate(xrange(triangle_x[x_min], triangle_x[x_max])):
# cartesian2barycentric(
# dst_x1, dst_y1, dst_x2, dst_y2, dst_x3, dst_y3, x, y, dst_loc
# )
#
# s = dst_loc[0]
# t = dst_loc[1]
#
# if s >= -0.001 and t >= -0.001 and s + t <= 1.001:
# L[0] = s
# L[1] = t
# L[2] = 1 - s - t
#
# src_loc = barycentric2cartesian(
# src_x1, src_x2, src_x3,
# src_y1, src_y2, src_y3,
# matrix,
# L
# )
#
# dst[y, x, :] = src[src_loc[1][0], src_loc[0][0], :]
#
@cython.boundscheck(False)
@cython.wraparound(False)
......@@ -170,15 +248,15 @@ def fill_triangle_src_dst(np.ndarray[unsigned char, ndim=3] src,
cdef np.ndarray matrix = np.full([3, 3], fill_value=1, dtype=DTYPE_int)
cdef np.ndarray src_loc = np.zeros([3, 1], dtype=DTYPE_float64)
cdef np.ndarray dst_loc = np.zeros([3, 1], dtype=DTYPE_float64)
cdef c_array.array dst_loc = c_array.array('f', [0., 0.])
for j, y in enumerate(xrange(triangle_y[y_min], triangle_y[y_max])):
for i, x in enumerate(xrange(triangle_x[x_min], triangle_x[x_max])):
dst_loc = cartesian2barycentric(
cartesian2barycentric(
triangle_x[0], triangle_y[0],
triangle_x[1], triangle_y[1],
triangle_x[2], triangle_y[2],
x, y
x, y, dst_loc
)
s = dst_loc[0]
......
src/reconstruction/texture_test.py
View file @ c2204dea
import cv2
import aam
import numpy as np
from .texture import cartesian2barycentric_slow_test, cartesian2barycentric_test
def test_cartesian2barycentricy():
blue_points = [[20, 20], [50, 160], [160, 20]]
x_1 = blue_points[0][0]
y_1 = blue_points[0][1]
x_2 = blue_points[1][0]
y_2 = blue_points[1][1]
x_3 = blue_points[2][0]
y_3 = blue_points[2][1]
x = 50
y = 70
lambdas_quick = cartesian2barycentric_test(x_1, y_1, x_2, y_2, x_3, y_3, x, y)
lambdas_quick = np.asarray(lambdas_quick)
lambdas_slow = cartesian2barycentric_slow_test(x_1, y_1, x_2, y_2, x_3, y_3, x, y)
np.testing.assert_array_equal(lambdas_quick, lambdas_slow)
def test_sample_from_triangles():
......@@ -16,32 +40,32 @@ def test_sample_from_triangles():
triangles = [[0, 1, 2]]
for tri in triangles:
cv2.line(blue_image,
tuple(blue_points[tri[0]]),
tuple(blue_points[tri[1]]), (0, 255, 0), 1)
cv2.line(blue_image,
tuple(blue_points[tri[1]]),
tuple(blue_points[tri[2]]), (0, 255, 0), 1)
cv2.line(blue_image,
tuple(blue_points[tri[2]]),
tuple(blue_points[tri[0]]), (0, 255, 0), 1)
for tri in triangles:
cv2.line(red_image,
tuple(red_points[tri[0]]),
tuple(red_points[tri[1]]), (0, 255, 0), 1)
cv2.line(red_image,
tuple(red_points[tri[1]]),
tuple(red_points[tri[2]]), (0, 255, 0), 1)
cv2.line(red_image,
tuple(red_points[tri[2]]),
tuple(red_points[tri[0]]), (0, 255, 0), 1)
all_triangles = aam.sample_from_triangles(
red_image, red_points, triangles
)
cv2.imshow('blue_image', blue_image)
cv2.imshow('red_image', red_image)
cv2.waitKey(0)
#for tri in triangles:
# cv2.line(blue_image,
# tuple(blue_points[tri[0]]),
# tuple(blue_points[tri[1]]), (0, 255, 0), 1)
# cv2.line(blue_image,
# tuple(blue_points[tri[1]]),
# tuple(blue_points[tri[2]]), (0, 255, 0), 1)
# cv2.line(blue_image,
# tuple(blue_points[tri[2]]),
# tuple(blue_points[tri[0]]), (0, 255, 0), 1)
#for tri in triangles:
# cv2.line(red_image,
# tuple(red_points[tri[0]]),
# tuple(red_points[tri[1]]), (0, 255, 0), 1)
# cv2.line(red_image,
# tuple(red_points[tri[1]]),
# tuple(red_points[tri[2]]), (0, 255, 0), 1)
# cv2.line(red_image,
# tuple(red_points[tri[2]]),
# tuple(red_points[tri[0]]), (0, 255, 0), 1)
#all_triangles = aam.sample_from_triangles(
# red_image, red_points, triangles
#)
#cv2.imshow('blue_image', blue_image)
#cv2.imshow('red_image', red_image)
#cv2.waitKey(0)
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