# the purpose of this code is to find fps
# so that we can figure out how does each detector/descriptor affect on fps rate
import cv2
import datetime
from myPackage.KeyPointDetectors import detectKeypoints
from myPackage.KeyPointsDescriptors import computeKeypoints
video = cv2.VideoCapture(0)
start = datetime.datetime.now()
numFrames = 0
while True:
isGrabbed, frame = video.read()
ORB = detectKeypoints(frame)
outputImage, keypoints = ORB.detectORB(True)
SURF = computeKeypoints(frame, keypoints)
kps, des = SURF.computeSURF()
cv2.imshow("Video", outputImage)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
numFrames += 1
fps = video.get(cv2.CAP_PROP_FPS)
print("fps is: {:.2f}".format(fps))
video.release()
end = datetime.datetime.now()
# the purpose of this code is to find fps
# so that we can figure out how does each detector/descriptor affect on fps rate
import cv2
import datetime
from myPackage.KeyPointDetectors import detectKeypoints
video = cv2.VideoCapture(0)
start = datetime.datetime.now()
numFrames = 0
while True:
isGrabbed, frame = video.read()
keypoints = detectKeypoints(frame)
outputImage = keypoints.detectSURF()
cv2.imshow("Video", outputImage)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
numFrames += 1
fps = video.get(cv2.CAP_PROP_FPS)
print("fps is: {:.2f}".format(fps))
video.release()
end = datetime.datetime.now()
frameRate = numFrames / (end - start).total_seconds()
print("Approximate fps is %(fps)d: " % {"fps": frameRate})
# the purpose of this code is to calculate the time needed to
# apply the detectors on different sets of images
from __future__ import print_function
from imutils import paths
from imutils.video import FPS
import cv2
from myPackage.KeyPointDetectors import detectKeypoints
import glob
totalTime = 0
for x in range(0, 99):
subTotalTime = 0
for imagePath in glob.glob("dataset/Images/Random/*"):
image = cv2.imread(imagePath)
fps = FPS().start()
keyPoints = detectKeypoints(image)
outputImage = keyPoints.detectFAST()
fps.stop()
subTotalTime = subTotalTime + fps.elapsed()
totalTime = totalTime + subTotalTime
print("Average elapsed time: ", totalTime / 100)
from __future__ import print_function
import argparse
from imutils import paths
from imutils.video import FPS
import cv2
from myPackage.KeyPointDetectors import detectKeypoints
ap = argparse.ArgumentParser()
ap.add_argument("-d", "--dataset", required=True, help="Path to the image")
args = vars(ap.parse_args())
imagePaths = list(paths.list_images(args["dataset"]))
fps = FPS().start()
for (i, imagePath) in enumerate(imagePaths):
filename = imagePath[imagePath.rfind("/") + 1:]
image = cv2.imread(imagePath)
SURF = detectKeypoints(image)
outputImage = SURF.detectSURF()
cv2.imshow("SIFT", outputImage)
cv2.waitKey()
fps.stop()
print("Elasped time: {:.2f}".format(fps.elapsed()))
# the purpose of this code is to calculate the time needed to
# apply the descriptors on different sets of images
from __future__ import print_function
from imutils import paths
from imutils.video import FPS
import cv2
from myPackage.KeyPointDetectors import detectKeypoints
from myPackage.KeyPointsDescriptors import computeKeypoints
import glob
totalTime = 0
for x in range(0, 99):
subTotalTime = 0
for imagePath in glob.glob("dataset/Images/Random/*"):
image = cv2.imread(imagePath)
ORB = detectKeypoints(image)
(outputImage, keypoints) = ORB.detectORB(True)
fps = FPS().start()
SURF = computeKeypoints(image, keypoints)
kps, des = SURF.computeSURF()
fps.stop()
subTotalTime = subTotalTime + fps.elapsed()
totalTime = totalTime + subTotalTime
print("Average elapsed time: ", totalTime / 100)
from __future__ import print_function
import argparse
import cv2
from imutils import paths
from imutils.video import FPS
from myPackage.KeyPointDetectors import detectKeypoints
ap = argparse.ArgumentParser()
ap.add_argument("-d", "--dataset", required=True, help="Path to the image")
args = vars(ap.parse_args())
imagePaths = list(paths.list_images(args["dataset"]))
fps = FPS().start()
for (i, imagePath) in enumerate(imagePaths):
filename = imagePath[imagePath.rfind("/") + 1:]
image = cv2.imread(imagePath)
HarrisKeyPoints = detectKeypoints(image)
outputImage = HarrisKeyPoints.detectHarris()
cv2.imshow("Harris", outputImage)
cv2.waitKey()
fps.stop()
print("Elasped time: {:.2f}".format(fps.elapsed()))
from __future__ import print_function
import argparse
from imutils import paths
from imutils.video import FPS
import cv2
from myPackage.KeyPointDetectors import detectKeypoints
ap = argparse.ArgumentParser()
ap.add_argument("-d", "--dataset", required=True, help="Path to the image")
args = vars(ap.parse_args())
imagePaths = list(paths.list_images(args["dataset"]))
fps = FPS().start()
for (i, imagePath) in enumerate(imagePaths):
filename = imagePath[imagePath.rfind("/") + 1:]
image = cv2.imread(imagePath)
SIFT = detectKeypoints(image)
outputImage = SIFT.detectSIFT()
cv2.imshow("SIFT", outputImage)
cv2.waitKey()
fps.stop()
print("Elasped time: {:.2f}".format(fps.elapsed()))
