# loop over the face parts individually
for (name, (i, j)) in face_utils.FACIAL_LANDMARKS_IDXS.items():
# clone the original image so we can draw on it, then
# display the name of the face part on the image
clone = frame.copy()
cv2.putText(clone, name, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
(0, 0, 255), 2)
# loop over the subset of facial landmarks, drawing the
# specific face part
for (x, y) in shape[i:j]:
cv2.circle(clone, (x, y), 1, (0, 0, 255), -1)
# extract the ROI of the face region as a separate image
(x, y, w, h) = cv2.boundingRect(np.array([shape[i:j]]))
roi = frame[y:y + h, x:x + w]
roi = imutils.resize(roi, width=250, inter=cv2.INTER_CUBIC)
# show the particular face part
cv2.imshow("ROI", roi)
cv2.imshow("Image", clone)
cv2.waitKey(0)
# visualize all facial landmarks with a transparent overlay
output = face_utils.visualize_facial_landmarks(frame, shape)
cv2.imshow("Image", output)
cv2.waitKey(0)
# # show the image
# cv2.imshow(winname="Face", mat=frame)
#
# # Exit when escape is pressed
# if cv2.waitKey(delay=1) == 27:
# break
while True:
counter = 0
extraSpace = 110
lineBarrier = 60
output = np.zeros((h + extraSpace, w * 2, 3), 'uint8')
timeStamps = np.zeros((2, 1))
if not np.count_nonzero(bkgd) and trackingToggle:
cv2.namedWindow('selectBackground')
cv2.setMouseCallback('selectBackground', buttonHandler)
bkgdOutput = np.zeros((h + extraSpace, w * 2, 3), 'uint8')
counter = 0
for stream in camList:
frame = stream.read()
frame = imutils.resize(frame, width=w, height=h)
bkgdOutput[0:h, w * counter:w * (counter + 1)] = frame
counter += 1
cv2.putText(bkgdOutput, 'Press the "1" key to take a background image',
(40, h + int(6 * extraSpace / 10)),
cv2.FONT_HERSHEY_SIMPLEX, .75, (255, 255, 255), 1)
overlay = bkgdOutput.copy()
bkgdOutputCopy = bkgdOutput.copy()
cv2.rectangle(overlay, (2 * w - 25, h - 25), (2 * w, h - 1),
(150, 150, 150), -1)
cv2.rectangle(overlay, (2 * w - 25, h - 25), (2 * w, h - 1),
(255, 255, 255), 1)
cv2.putText(overlay, '< >', (2 * w - 20, h - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.25, (255, 255, 255), 2)
cv2.addWeighted(overlay, buttonAlpha, bkgdOutputCopy, 1 - buttonAlpha,
import numpy as np
import cv2
from imutils import imutils
# translations
image = cv2.imread(
"/home/mmc/code/python_opencv/Books/Practical Python and OpenCV, 3rd Edition/code/images/trex.png"
)
M = np.float32([[1, 0, 25], [0, 1, 50]])
shifted = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Down and Right", shifted)
M = np.float32([[1, 0, -50], [0, 1, -90]])
shifted = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Up and Left", shifted)
shifted = imutils.translate(image, 0, 100)
cv2.imshow('Shifted Down', shifted)
cv2.imshow('Original', image)
im_resized = imutils.resize(image, width=100)
cv2.imshow('Resized', im_resized)