#!/usr/bin/python3
import numpy as np
import cv2
cam = cv2.VideoCapture(0)
#deciding video format
vid_format = cv2.VideoWriter_fourcc(*'xvid')
#filename ,video format,FPS,video W,H
out = cv2.VideoWriter('output.avi', vid_format, 5.0, (640, 480))
print(cv2.get(cv2.CAP_PROP_FRAME_WIDTH))
print(cv2.get(cv2.CAP_PROP_FRAME_HEIGHT))
while cam.isOpened():
status, frame = cam.read()
cv2.imshow('frame', frame)
out.write(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not frame:
break
cv2.imshow('video', frame)
key = cv2.waitKey()
if key == 27:
break
cap.release()
cv2.destroyAllWindow()
''' Time and Date '''
cap = cv2.VideoCapture(0)
print(cv2.get(3))
print(cv2.get(4))
while (cap.isOpened()):
ret, frame = cap.read()
if ret == True:
font = cv2.FONT_HERSHEY_SIMPLEX
text = 'Width:' + str(cap.get(3)) + 'Height:' + str(cap.get(4))
frame = cv2.putText(frame, text, (10, 50), font, 5, (0, 0, 255), cv2.Line_AA)
date = str(datetime.datetime.now())
frame = cv2.putText(frame, date, (10, 50), font, 5, (0, 0, 255), cv2.Line_AA)
cap.release()
cv2.destroyAllWindows()
''' Arithmetic operation on images'''
def getFrame(self,
vid_file,
frame_index,
gray=False,
flatten=False,
dtype=None,
resize_shape=None,
reshape_image=None,
augmentation=False):
cap = cv2.VideoCapture(vid_file)
if (cap.set(1, frame_index) == False):
print(
"ERROR in PrepareDataset/getFrame: Setting video file pointer failed"
)
print("vid_file =", vid_file)
print("frame_index =", frame_index)
print("total frames =", cv2.get(cv2.CAP_PROP_FRAME_COUNT))
exit(0)
ret, frame = cap.read()
if (ret == False):
print(
"ERROR in PrepareDataset/getFrame: Reading video file frame failed"
)
print("vid_file =", vid_file)
print("frame_index =", frame_index)
print("total frames =", cv2.get(cv2.CAP_PROP_FRAME_COUNT))
exit(0)
cap.release()
if (augmentation == True):
rotation_list = [
np.random.randint(-self.rotation_higher_index,
-self.rotation_lower_index) / 100,
np.random.randint(self.rotation_lower_index,
self.rotation_higher_index) / 100
]
params = {
'theta':
np.random.choice(rotation_list),
'brightness':
np.random.randint(self.brightness_lower_index,
self.brightness_higher_index) / 100
}
frame = self.augmentation_object.apply_transform(
x=frame, transform_parameters=params).astype(frame.dtype)
if (gray == True):
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
if (resize_shape != None):
frame = self.resize_image(frame, resize_shape, print_it=False)
if (flatten == True and reshape_image != None):
print(
"Warning: flatten and reshape used together. Make sure you know what you are doing"
)
if (flatten == True):
frame = frame.flatten()
if (reshape_image != None):
frame = frame.reshape(reshape_image)
if (dtype == None):
return frame
return frame.astype(dtype)
sound = mixer.Sound('alarm.wav')
face = cv2.CascadeClassifier(
'haar cascade files\haarcascade_frontalface_alt.xml')
leye = cv2.CascadeClassifier(
'haar cascade files\haarcascade_lefteye_2splits.xml')
reye = cv2.CascadeClassifier(
'haar cascade files\haarcascade_righteye_2splits.xml')
lbl = ['Close', 'Open']
model = load_model('cnnCat2.h5')
path = os.getcwd()
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
nbFrames = cv2.get(Videoio.CAP_PROP_FRAME_COUNT)
count = 0
score = 0
thicc = 2
rpred = [99]
lpred = [99]
while (True):
ret, frame = cap.read()
height, width = frame.shape[:2]
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face.detectMultiScale(gray,
minNeighbors=5,
scaleFactor=1.1,
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 21 14:54:25 2020
@author: krypton
"""
#%% imports
import cv2
#%%
cap = cv2.VideoCapture(0)
width = cv2.get(cv2.CAP_PROP_FRAME_WIDTH)
height = cv2.get(cv2.CAP_PROP_FRAME_HEIGHT)
#%%
while True:
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow("video", gray)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
cap.release()
cv2.destroyAllWindows()
args = vars(ap.parse_args())
greenLower = (29, 86, 6)
greenUpper = (64, 255, 255)
pts = deque(maxlen=args['buffer'])
if not args.get("video", False):
cap = VideoStream(src=0).start()
else:
cap = cv2.VideoCapture(args["video"])
time.sleep(2.0)
#Globals
thickness_amt = 5
height = int(cv2.get(cv2.CAP_PROP_FRAME_HEIGHT))
width = int(cv2.get(cv2.CAP_PROP_FRAME_WIDTH))
print(height)
print(width)
while (1):
# Take each frame
frame = cap.read()
frame = cv2.flip(frame, 1)
frame = frame[1] if args.get("video", False) else frame
if frame is None:
break
import cv2
import time
if __name__ == '__main__':
# Start default camera
video = cv2.VideoCapture(0)
fps = video.get(cv2.CAP_PROP_FPS)
print("Frames per second using video.get(cv2.cv.CV_CAP_PROP_FPS): {0}".format(fps))
num_frames = 120
print("Capturing {0} frames".format(num_frames))
# Start time
start = cv2.get()
# Grab a few frames
for i in range(0, num_frames):
ret, frame = video.read()
# End time
end = time.time()
# Time elapsed
seconds = end - start
print("Time taken : {0} seconds".format(seconds))
# Calculate frames per second
fps = num_frames / seconds;
print("Estimated frames per second : {0}".format(fps))