def run():
cap = cv2.VideoCapture(0)
save_path = 'saved-media/glasses_and_stash.mp4'
frames_per_seconds = 24
config = CFEVideoConf(cap, filepath=save_path, res='720p')
out = cv2.VideoWriter(save_path, config.video_type, frames_per_seconds,
config.dims)
face_cascade = cv2.CascadeClassifier(
'cascades/data/haarcascade_frontalface_default.xml')
eyes_cascade = cv2.CascadeClassifier(
'cascades/third-party/frontalEyes35x16.xml')
nose_cascade = cv2.CascadeClassifier('cascades/third-party/Nose18x15.xml')
glasses = cv2.imread("images/glasses/11.png", -1)
mustache = cv2.imread("images/mustache/mustache.png", -1)
imgHair = cv2.imread('images/hair/2.png', -1)
while (True):
# Capture frame-by-frame
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray,
scaleFactor=1.5,
minNeighbors=5)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA)
for (x, y, w, h) in faces:
y = y - 70
roi_gray = gray[y:y + h, x:x + h] # rec
roi_color = frame[y:y + h, x:x + h]
#cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 255, 255), 3)
eyes = eyes_cascade.detectMultiScale(roi_gray,
scaleFactor=1.5,
minNeighbors=5)
for (ex, ey, ew, eh) in eyes:
#cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 3)
roi_eyes = roi_gray[ey:ey + eh, ex:ex + ew]
glasses2 = image_resize(glasses.copy(), width=ew)
gw, gh, gc = glasses2.shape
for i in range(0, gw):
for j in range(0, gh):
#print(glasses[i, j]) #RGBA
if glasses2[i, j][3] != 0: # alpha 0
roi_color[ey + i, ex + j] = glasses2[i, j]
nose = nose_cascade.detectMultiScale(roi_gray,
scaleFactor=1.5,
minNeighbors=5)
for (nx, ny, nw, nh) in nose:
#cv2.rectangle(roi_color, (nx, ny), (nx + nw, ny + nh), (255, 0, 0), 3)
roi_nose = roi_gray[ny:ny + nh, nx:nx + nw]
mustache2 = image_resize(mustache.copy(), width=nw)
mw, mh, mc = mustache2.shape
for i in range(0, mw):
for j in range(0, mh):
#print(glasses[i, j]) #RGBA
if mustache2[i, j][3] != 0: # alpha 0
roi_color[ny + int(nh / 3.0) + i,
nx + j] = mustache2[i, j]
face = face_cascade.detectMultiScale(roi_gray,
scaleFactor=1.5,
minNeighbors=5)
for (fx, fy, fw, fh) in face:
fx = fx - 40
fy = fy - 120
#cv2.rectangle(roi_color, (fx, fy), (fx + fw, fy + fh), (255, 0, 0), 3)
roi_face = roi_gray[fy:fy + fh, fx:fx + fw]
imgHair2 = image_resize(imgHair.copy(), width=fw + int(fw / 6))
hw, hh, hc = imgHair2.shape
for i in range(0, hw):
for j in range(0, hh):
#print(glasses[i, j]) #RGBA
if imgHair2[i, j][3] != 0: # alpha 0
roi_color[fy + i, fx + j] = imgHair2[i, j]
# Display the resulting frame
frame = cv2.cvtColor(frame, cv2.COLOR_BGRA2BGR)
out.write(frame)
cv2.imshow('frame', frame)
if cv2.waitKey(20) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
out.release()
cv2.destroyAllWindows()
import numpy as np
import cv2
from utils import CFEVideoConf, image_resize
cap = cv2.VideoCapture(0)
save_path = 'saved-media/watermark.mp4'
frames_per_seconds = 24
config = CFEVideoConf(cap, filepath=save_path, res='720p')
out = cv2.VideoWriter(save_path, config.video_type, frames_per_seconds,
config.dims)
img_path = 'images/logo/cfe-coffee.png'
logo = cv2.imread(img_path, -1)
watermark = image_resize(logo, height=50)
#watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2GRAY)
#watermark = cv2.cvtColor(watermark, cv2.COLOR_GRAY2BGR)
watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2BGRA)
# grayscale watermark
# cv2.imshow('watermark', watermark)
#print(watermark.shape)
while (True):
# Capture frame-by-frame
ret, frame = cap.read()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA)
# print(frame[50, 150]) # numpy array
# start_cord_x = 50
# start_cord_y = 150
in_vid = cv2.VideoCapture('example.mp4')
img_dir = "Frames"
seconds_duration = 16
seconds_between_shots = .35
try:
if not os.path.exists(img_dir):
os.makedirs(img_dir)
except OSError:
print('Error: Creating directory of frames')
now = datetime.datetime.now()
finish_time = now + datetime.timedelta(seconds=seconds_duration)
currentFrame = 0
frame_rate = 40
save_path = 'output.mp4'
config = CFEVideoConf(in_vid, filepath=save_path, res='720p')
out = cv2.VideoWriter(save_path, config.video_type, frame_rate, config.dims)
while datetime.datetime.now() < finish_time:
ret, frame = in_vid.read()
filename = f"{img_dir}/{currentFrame}.jpg"
currentFrame += 1
cv2.imwrite(filename, frame)
time.sleep(seconds_between_shots)
# Combine images to Video
image_list = glob.glob(f"{img_dir}/*.jpg")
for file in image_list:
image_frame = cv2.imread(file)
image = image_resize(image_frame, width=config.width)
out.write(image)
import numpy as np
import cv2
from utils import CFEVideoConf, image_resize
filename = 'watermark.mp4'
frames_per_seconds = 24.0
cap = cv2.VideoCapture(0)
config = CFEVideoConf(cap, filepath=filename, res='720p')
out = cv2.VideoWriter(filename, config.video_type, frames_per_seconds,
config.dims)
watermark = 'Marketing-Communications-Logo-1.png'
image = cv2.imread(watermark, -1)
image = image_resize(image, 100, 100)
cv2.imshow('watermark', image)
while True:
ret, frame = cap.read()
out.write(frame)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
out.release()
cv2.destroyAllWindows()
from utils import CFEVideoConf, image_resize import glob import math import cv2 import numpy as np cap = cv2.VideoCapture(0) framesPerSecond = 24.0 savePath = 'filter.mp4' config = CFEVideoConf(cap, filepath=savePath, res='480p') # Filters def applyInvert(frame): return cv2.bitwise_not(frame) def verifyAlphaChannel(frame): try: frame.shape[3] except IndexError: frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA) return frame def applyColor(frame, intensity=0.2, blue=0, green=0, red=0): frame = verifyAlphaChannel(frame) frameH, frameW, frameC = frame.shape sepiaBGRA = (blue, green, red, 1) overlay = np.full((frameH, frameW, 4), sepiaBGRA, dtype='uint8')
import numpy as np
import os
import cv2
#WEBCAM MAX RES 640 x 480
from utils import CFEVideoConf, image_resize
cap = cv2.VideoCapture(0)
save_path = 'saved-media/watermark.mp4'
frames_per_second = 24
config = CFEVideoConf(cap, filepath=save_path, res='480')
out = cv2.VideoWriter(save_path, config.video_type, frames_per_second,
config.dims)
img_path = 'logo.jpg'
logo = cv2.imread(img_path, -1)
watermark = image_resize(logo, height=50)
cv2.imshow('watermark', watermark)
while (True):
# capture frame by frame
ret, frame = cap.read()
# out.write(frame)
# display the frame
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
import numpy as np
import cv2
from utils import CFEVideoConf, image_resize
cap = cv2.VideoCapture(0)
save_path = 'g:/videos/watermark.mp4'
frames_per_seconds = 24
config = CFEVideoConf(cap, filepath=save_path, res='480p') # used to change the resolution
out = cv2.VideoWriter(save_path, config.video_type, frames_per_seconds, config.dims)
img_path = 'G:\pictures/cats.png'
logo = cv2.imread(img_path,-1)
#watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2BGRA)
watermark = image_resize(logo, height = 100) # gray scale, do not have number 3
watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2BGRA) #has number 3
#cv2.imshow('watermark', watermark)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA)
# used to demonstrate
# start_cord_x = 50
# start_cord_y = 150
# stroke = 2
# color = [255,255,0]
# w = 100
# h = 200