def main(video, saveLocation):
# start_time = time.time()
# creating the review file to be written to
directory_1 = saveLocation + '/review_settings.csv'
review_file = open(directory_1, 'w', newline='')
writer = csv.writer(review_file)
header = ['Effect','Contact','Intensity','PulseWidth','Frequency','Impedance','TargetLocation','StimulationONOFF']
writer.writerow(header)
review_file.close()
# create a patient limits new csv file to be written to
directory_2 = saveLocation + '/patient_limits.csv'
limits_file = open(directory_2, 'w', newline='')
writer = csv.writer(limits_file)
header = ['StepSize', 'Minimum', 'Maximum']
writer.writerow(header)
limits_file.close()
ReadVideo.main(video, directory_1, directory_2)
def testSpatialAlignmentEvangelidis(self):
"""
We test Evangelidis Spatial Alignment, given the precomputed
temporal alignment, the cross array.
"""
videoPathFileNameQ = "Videos/input.avi"
videoPathFileNameR = "Videos/reference.avi"
"""
We want to use the same JPEGs Matlab is using - since the algorithm
is somewhat sensitive to quantisation errors.
"""
assert config.TESTING_IDENTICAL_MATLAB == True
import ReadVideo
captureQ, frameCountQ, resVidQ = ReadVideo.OpenVideoCapture(
videoPathFileNameQ, 0)
common.DebugPrint("Alex: frameCountQ = %d" % frameCountQ)
captureR, frameCountR, resVidR = ReadVideo.OpenVideoCapture(
videoPathFileNameR, 1)
common.DebugPrint("Alex: frameCountR = %d" % frameCountR)
"""
The cross result we obtain for the videos from
Evangelidis, with step=25 (1fps).
"""
crossref = [[0, 48], [1, 48], [2, 48], [3, 48], [4, 48], [5, 48],
[6, 0], [7, 0], [8, 60], [9, 60], [10, 60], [11, 60],
[12, 67], [13, 67], [14, 67], [15, 67], [16, 67], [17, 67],
[18, 72], [19, 72], [20, 72], [21, 78], [22, 78], [23, 78],
[24, 78], [25, 78], [26, 82], [27, 82], [28, 82], [29, 54],
[30, 54]]
crossref = np.array(crossref)
#SpatialAlignmentEvangelidis(cross, captureQ=None, captureR=None);
res = SpatialAlignmentEvangelidis(crossref, captureQ, captureR)
common.DebugPrint("Corrected cross from SpatialAlignmentEvangelidis() = %s" % \
str(res))
"""
common.DebugPrint("cv2.getNumThreads() (#logical CPUs) is %s" % str(cv2.getNumThreads()));
"""
videoPathFileNameQ = sys.argv[1]; # input/current video
videoPathFileNameR = sys.argv[2]; # reference video
#!!!!TODO: use getopt() to run Evangelidis' or "Alex's" algorithm, etc
#if True:
if False:
import hotshot
prof = hotshot.Profile("hotshot_edi_stats_Main");
#prof.runcall(findquads, Points, threshold, reflect_flag);
prof.runcall(ReadVideo.Main, videoPathFileNameQ, videoPathFileNameR);
print;
prof.close();
"""
from hotshot import stats
s = stats.load("hotshot_edi_stats_findquads");
s.sort_stats("time").print_stats();
#s.print_stats()
"""
else:
ReadVideo.Main(videoPathFileNameQ, videoPathFileNameR);
def main(argv):
assert len(sys.argv) >= 3
if FLAGS.preprocess_ref:
config.PREPROCESS_REFERENCE_VIDEO_ONLY = True
elif FLAGS.process_query_and_align_videos:
config.PREPROCESS_REFERENCE_VIDEO_ONLY = False
else:
config.PREPROCESS_REFERENCE_VIDEO_ONLY = False
print("config.PREPROCESS_REFERENCE_VIDEO_ONLY = %s" % str(
config.PREPROCESS_REFERENCE_VIDEO_ONLY))
ask_first()
# Inspired from https://stackoverflow.com/questions/1520234/how-to-check-which-version-of-numpy-im-using
print("numpy.version.version = %s" % str(np.version.version))
print("scipy.version.version = %s" % str(scipy.version.version))
np.show_config()
scipy.show_config()
# See http://docs.scipy.org/doc/numpy/reference/generated/numpy.set_printoptions.html
# We use 7 digits precision and suppress using scientific notation.
np.set_printoptions(precision=7, suppress=True,
threshold=70000, linewidth=4000)
# Inspired from \OpenCV2-Python-Tutorials-master\source\py_tutorials\py_core\py_optimization
# normally returns True - relates to using the SIMD extensions of x86:
# SSX, AVX
common.DebugPrint("cv2.useOptimized() is %s" % str(cv2.useOptimized()))
"""
From http://docs.opencv.org/modules/core/doc/utility_and_system_functions_and_macros.html#checkhardwaresupport
CV_CPU_MMX - MMX
CV_CPU_SSE - SSE
CV_CPU_SSE2 - SSE 2
CV_CPU_SSE3 - SSE 3
CV_CPU_SSSE3 - SSSE 3
CV_CPU_SSE4_1 - SSE 4.1
CV_CPU_SSE4_2 - SSE 4.2
CV_CPU_POPCNT - POPCOUNT
CV_CPU_AVX - AVX
"""
# TODO: Figure out the correct way to reference these in OpenCV 3.x
"""
# Need to setUseOptimized before calling checkHardwareSupport
cv2.setUseOptimized(True)
if config.OCV_OLD_PY_BINDINGS == False:
featDict = {cv2.CpuFeatures.CV_CPU_AVX: "AVX",
cv2.CPU_MMX: "MMX",
cv2.CPU_NEON: "NEON",
cv2.CPU_POPCNT: "POPCNT",
cv2.CPU_SSE: "SSE",
cv2.CPU_SSE2: "SSE2",
cv2.CPU_SSE3: "SSE3",
cv2.CPU_SSE4_1: "SSE4.1",
cv2.CPU_SSE4_2: "SSE4.2",
cv2.CPU_SSSE3: "SSSE3"}
for feat in featDict:
res = cv2.checkHardwareSupport(feat)
print("%s = %d" % (featDict[feat], res))
"""
# "Returns the number of logical CPUs available for the process."
common.DebugPrint("cv2.getNumberOfCPUs() (#logical CPUs) is %s" % str(
cv2.getNumberOfCPUs()))
common.DebugPrint(
"cv2.getTickFrequency() is %s" % str(cv2.getTickFrequency()))
video_file_q = sys.argv[1] # input/current video
video_file_r = sys.argv[2] # reference video
# TODO: use getopt() to run Evangelidis' or "Alex's" algorithm, etc
ReadVideo.main(video_file_q, video_file_r)
name_of_video = os.path.splitext(args.video)[0] # name of video without file extension
path_video = PATH_TO_VIDEO + args.video
if not os.path.exists(path_video):
log.error(" %s didn't find" % path_video)
exit(1)
else:
name_of_video = 'online_camera'
path_video = args.video
if args.filename == 'no': # if name of file with txt doesn't point - it will be name of video
filename = name_of_video + '.txt'
else:
filename = args.filename
if args.sec == '0':
sec = 0.1
else:
sec = float(args.sec)
return path_video, filename, name_of_video, sec
if __name__ == '__main__':
parser = create_parser()
args = parser.parse_args()
path_video, filename, name_of_video, sec = parse_args(args)
log.info(' Run video %s' % args.video)
ReadVideo.read_video(path_video, filename, args.type, name_of_video, sec, args.frame)
log.info(' Close video %s \n\n' % args.video)
def TestGoProCameraVideos():
"""
Running Spatial Alignment, given the precomputed
temporal alignment, the cross array.
"""
path = "/home/asusu/drone-diff_Videos/GoPro_clips/2HD_cuts_from_Lucian/"
videoPathFileNameQ = path + "GOPR7269_50-55.MP4"
videoPathFileNameR = path + "GOPR7344_90-95.MP4"
import ReadVideo
captureQ, frameCountQ, resVidQ = ReadVideo.OpenVideoCapture(
videoPathFileNameQ, 0)
common.DebugPrint("Alex: frameCountQ = %d" % frameCountQ)
captureR, frameCountR, resVidR = ReadVideo.OpenVideoCapture(
videoPathFileNameR, 1)
common.DebugPrint("Alex: frameCountR = %d" % frameCountR)
"""
crossref = np.array([ \
[ 7, 120],
[ 8, 120],
[ 9, 120],
[ 10, 120],
[ 11, 120],
[ 12, 120],
[ 13, 120],
[ 14, 120],
[ 15, 120],
[ 16, 120],
[ 17, 120],
[ 18, 120],
[ 19, 114],
[ 20, 4],
[ 21, 4],
[ 22, 5],
[ 23, 5],
[ 24, 5],
[ 25, 4],
[ 26, 4],
[ 27, 4],
[ 28, 4],
[ 29, 4],
[ 30, 4],
[ 31, 4],
[ 32, 4],
[ 33, 4],
[ 34, 4],
[ 35, 4],
[ 36, 4],
[ 37, 4],
[ 38, 0],
[ 39, 0],
[ 40, 0],
[ 41, 5],
[ 42, 5],
[ 43, 5],
[ 44, 5],
[ 45, 5],
[ 46, 5],
[ 47, 5],
[ 48, 5],
[ 49, 5],
[ 50, 5],
[ 51, 5],
[ 52, 5],
[ 53, 5],
[ 54, 5],
[ 55, 6],
[ 56, 6],
[ 57, 6],
[ 58, 6],
[ 59, 6],
[ 60, 6],
[ 61, 6],
[ 62, 6],
[ 63, 6],
[ 64, 6],
[ 65, 78],
[ 66, 6],
[ 67, 6],
[ 68, 6],
[ 69, 6],
[ 70, 6],
[ 71, 6],
[ 72, 6],
[ 73, 6],
[ 74, 7],
[ 75, 7],
[ 76, 7],
[ 77, 7],
[ 78, 7],
[ 79, 7],
[ 80, 13],
[ 81, 12],
[ 82, 12],
[ 83, 12],
[ 84, 12],
[ 85, 16],
[ 86, 16],
[ 87, 16],
[ 88, 15],
[ 89, 22],
[ 90, 22],
[ 91, 22],
[ 92, 22],
[ 93, 22],
[ 94, 22],
[ 95, 22],
[ 96, 22],
[ 97, 22],
[ 98, 22],
[ 99, 32],
[100, 32],
[101, 32],
[102, 32],
[103, 32],
[104, 33],
[105, 34],
[106, 34],
[107, 34],
[108, 38],
[109, 38],
[110, 38],
[111, 38],
[112, 43],
[113, 43],
[114, 43],
[115, 43],
[116, 43],
[117, 45],
[118, 41],
[119, 60],
[120, 60],
[121, 60],
[122, 60],
[123, 60],
[124, 60],
[125, 60],
[126, 60],
[127, 60],
[128, 60],
[129, 60],
[130, 60],
[131, 60],
[132, 60],
[133, 60],
[ 0, 4],
[ 1, 4],
[ 2, 4],
[ 3, 4],
[ 4, 4],
[ 5, 4],
[ 6, 4]]);
"""
crossref = np.array([ \
[ 7, 120],
[ 8, 120],
[ 9, 120],
[ 10, 120],
[ 11, 120],
[ 12, 120],
[ 13, 120],
[ 14, 120],
[ 15, 120],
[ 16, 120],
[ 17, 120],
[ 18, 120],
[ 19, 114],
[ 20, 4],
[ 21, 4],
[ 22, 5],
[ 23, 5],
[ 24, 5],
[ 25, 4],
[ 26, 4],
[ 27, 4],
[ 28, 4],
[ 29, 4],
[ 30, 4],
[ 31, 4],
[ 32, 4],
[ 33, 4],
[ 34, 4],
[ 35, 4],
[ 36, 4],
[ 37, 4],
[ 38, 0],
[ 39, 0],
[ 40, 0],
[ 41, 5],
[ 42, 5],
[ 43, 5],
[ 44, 5],
[ 45, 5],
[ 46, 5],
[ 47, 5],
[ 48, 5],
[ 49, 5],
[ 50, 5],
[ 51, 5],
[ 52, 5],
[ 53, 5],
[ 54, 5],
[ 55, 6],
[ 56, 6],
[ 57, 6],
[ 58, 6],
[ 59, 6],
[ 60, 6],
[ 61, 6],
[ 62, 6],
[ 63, 6],
[ 64, 6],
[ 65, 78],
[ 66, 6],
[ 67, 6],
[ 68, 6],
[ 69, 6],
[ 70, 6],
[ 71, 6],
[ 72, 6],
[ 73, 6],
[ 74, 7],
[ 75, 7],
[ 76, 7],
[ 77, 7],
[ 78, 7],
[ 79, 7],
[ 80, 13],
[ 81, 12],
[ 82, 12],
[ 83, 12],
[ 84, 12],
[ 85, 16],
[ 86, 16],
[ 87, 16],
[ 88, 15],
[ 89, 22],
[ 90, 22],
[ 91, 22],
[ 92, 22],
[ 93, 22],
[ 94, 22],
[ 95, 22],
[ 96, 22],
[ 97, 22],
[ 98, 22],
[ 99, 32],
[100, 32],
[101, 32],
[102, 32],
[103, 32],
[104, 33],
[105, 34],
[106, 34],
[107, 34],
[108, 38],
[109, 38],
[110, 38],
[111, 38],
[112, 43],
[113, 43],
[114, 43],
[115, 43],
[116, 43],
[117, 45],
[118, 41],
[119, 60],
[120, 60],
[121, 60],
[122, 60],
[123, 60],
[124, 60],
[125, 60],
[126, 60],
[127, 60],
[128, 60],
[129, 60],
[130, 60],
[131, 60],
[132, 60],
[133, 60],
[ 0, 4],
[ 1, 4],
[ 2, 4],
[ 3, 4],
[ 4, 4],
[ 5, 4],
[ 6, 4]])
res = SpatialAlignmentEvangelidis(crossref, captureQ, captureR)
print("Corrected cross from SpatialAlignmentEvangelidis() = %s" % \
str(res))