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cv_utils.py
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cv_utils.py
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# Source: https://learnopencv.com
# Copyright (c) 2016 Satya Mallick <[email protected]>
# All rights reserved. No warranty, explicit or implicit, provided.
from imutils.face_utils import FaceAligner
from imutils.face_utils import rect_to_bb
from imutils import face_utils
import pandas as pd
import numpy as np
import cv2 as cv
import random
def readPoints(path):
'''Read points from .tem file'''
# Create an array of points.
points = []
# Read points
with open(path) as file:
no_lines = int(file.readline())
for i, line in enumerate(file):
if 0 <= i < no_lines:
x, y = line.split()
points.append((int(float(x)), int(float(y))))
return points
def applyAffineTransform(src, srcTri, dstTri, size):
'''Apply affine transform calculated using srcTri and dstTri to src and output an image of size.'''
# Given a pair of triangles, find the affine transform.
warpMat = cv.getAffineTransform(np.float32(srcTri), np.float32(dstTri))
# Apply the Affine Transform just found to the src image
dst = cv.warpAffine(src, warpMat, (size[0], size[1]), None,
flags=cv.INTER_LINEAR, borderMode=cv.BORDER_REFLECT_101)
return dst
def morphTriangle(img1, img2, img, t1, t2, t, alpha):
'''Warps and alpha blends triangular regions from img1 and img2 to img'''
# Find bounding rectangle for each triangle
r1 = cv.boundingRect(np.float32([t1]))
r2 = cv.boundingRect(np.float32([t2]))
r = cv.boundingRect(np.float32([t]))
# Offset points by left top corner of the respective rectangles
t1Rect = []
t2Rect = []
tRect = []
for i in range(0, 3):
tRect.append(((t[i][0] - r[0]), (t[i][1] - r[1])))
t1Rect.append(((t1[i][0] - r1[0]), (t1[i][1] - r1[1])))
t2Rect.append(((t2[i][0] - r2[0]), (t2[i][1] - r2[1])))
# Get mask by filling triangle
mask = np.zeros((r[3], r[2], 3), dtype=np.float32)
cv.fillConvexPoly(mask, np.int32(tRect), (1.0, 1.0, 1.0), 16, 0)
# Apply warpImage to small rectangular patches
img1Rect = img1[r1[1]:r1[1] + r1[3], r1[0]:r1[0] + r1[2]]
img2Rect = img2[r2[1]:r2[1] + r2[3], r2[0]:r2[0] + r2[2]]
size = (r[2], r[3])
warpImage1 = applyAffineTransform(img1Rect, t1Rect, tRect, size)
warpImage2 = applyAffineTransform(img2Rect, t2Rect, tRect, size)
# Alpha blend rectangular patches
imgRect = (1.0 - alpha) * warpImage1 + alpha * warpImage2
# Copy triangular region of the rectangular patch to the output image
img[r[1]:r[1]+r[3], r[0]:r[0]+r[2]] = img[r[1]:r[1] +
r[3], r[0]:r[0]+r[2]] * (1 - mask) + imgRect * mask
def rect_contains(rect, point):
'''Check if a point is inside a rectangle'''
if point[0] < rect[0]:
return False
elif point[1] < rect[1]:
return False
elif point[0] > rect[2]:
return False
elif point[1] > rect[3]:
return False
return True
def draw_point(img, p, color):
'''Draw a point'''
cv.circle(img, p, 2, color, cv.FILLED, cv.LINE_AA, 0)
def draw_voronoi(img, subdiv):
'''Draw voronoi diagram'''
(facets, centers) = subdiv.getVoronoiFacetList([])
for i in range(0, len(facets)):
ifacet_arr = []
for f in facets[i]:
ifacet_arr.append(f)
ifacet = np.array(ifacet_arr, np.int)
color = (random.randint(0, 255), random.randint(
0, 255), random.randint(0, 255))
cv.fillConvexPoly(img, ifacet, color, cv.LINE_AA, 0)
ifacets = np.array([ifacet])
cv.polylines(img, ifacets, True, (0, 0, 0), 1, cv.LINE_AA, 0)
cv.circle(img, (centers[i][0], centers[i][1]),
3, (0, 0, 0), cv.FILLED, cv.LINE_AA, 0)
def draw_delaunay(img, subdiv, delaunay_color):
'''Draw delaunay triangles'''
triangleList = subdiv.getTriangleList()
size = img.shape
r = (0, 0, size[1], size[0])
for t in triangleList:
pt1 = (t[0], t[1])
pt2 = (t[2], t[3])
pt3 = (t[4], t[5])
if rect_contains(r, pt1) and rect_contains(r, pt2) and rect_contains(r, pt3):
cv.line(img, pt1, pt2, delaunay_color, 1, cv.LINE_AA, 0)
cv.line(img, pt2, pt3, delaunay_color, 1, cv.LINE_AA, 0)
cv.line(img, pt3, pt1, delaunay_color, 1, cv.LINE_AA, 0)
def calculateDelaunayTriangles(rect, subdiv, points, img, win_delaunay, delaunay_color, draw=False):
'''Calculate delanauy triangle'''
# Insert points into subdiv
for p in points:
subdiv.insert((p[0], p[1]))
# List of triangles. Each triangle is a list of 3 points (6 numbers)
triangleList = subdiv.getTriangleList()
# Find the indices of triangles in the points array
delaunayTri = []
for t in triangleList:
pt = []
pt.append((t[0], t[1]))
pt.append((t[2], t[3]))
pt.append((t[4], t[5]))
pt1 = (t[0], t[1])
pt2 = (t[2], t[3])
pt3 = (t[4], t[5])
if rect_contains(rect, pt1) and rect_contains(rect, pt2) and rect_contains(rect, pt3):
ind = []
for j in range(0, 3):
for k in range(0, len(points)):
if(abs(pt[j][0] - points[k][0]) < 0.1 and abs(pt[j][1] - points[k][1]) < 0.5):
ind.append(k)
if len(ind) == 3:
delaunayTri.append((ind[0], ind[1], ind[2]))
# Draw lines
if draw:
cv.line(img, pt1, pt2, delaunay_color, 1, cv.LINE_AA, 0)
cv.line(img, pt2, pt3, delaunay_color, 1, cv.LINE_AA, 0)
cv.line(img, pt3, pt1, delaunay_color, 1, cv.LINE_AA, 0)
imgS = cv.resize(img, (413, 531))
return delaunayTri
def drawLanmarks(rect, points, img, col):
(x, y, w, h) = face_utils.rect_to_bb(rect)
for (x, y) in points:
cv.circle(img, (x, y), 2, col, -1)
def readPermutations(file, header, footer):
data = pd.read_csv(file)
return data.apply(lambda x: header + x + footer).values