def main():
'''
Parse command line arguments and execute the code
'''
start = time.time()
parser = argparse.ArgumentParser()
parser.add_argument('--det_frames_folder', default='det_frames/', type=str)
parser.add_argument('--det_result_folder',
default='det_results/',
type=str)
parser.add_argument('--result_folder', default='summary_result/', type=str)
parser.add_argument('--summary_file', default='results.txt', type=str)
parser.add_argument('--output_name', default='output.mp4', type=str)
parser.add_argument('--perc', default=100, type=int)
#parser.add_argument('--path_video', dest='path_video', required=True, type=str)
parser.add_argument('--path_video', dest='path_video', type=str)
args = parser.parse_args()
args.path_video = './DAVIS-2017-TrainVal.mp4'
#with tf.device('/gpu:0'):
frame_list, frames = Utils_Video.extract_frames(args.path_video, args.perc)
det_frame_list, det_result_list = still_image_YOLO_DET(
frame_list, frames, args.det_frames_folder, args.det_result_folder)
Utils_Video.make_video_from_list(args.output_name, det_frame_list)
print_YOLO_DET_result(det_result_list, args.result_folder,
args.summary_file)
end = time.time()
print("Elapsed Time:%d Seconds" % (end - start))
print("Running Completed with Success!!!")
def main():
'''
Parse command line arguments and execute the code
'''
start = time.time()
parser = argparse.ArgumentParser()
parser.add_argument('--det_frames_folder', default='det_frames/', type=str)
parser.add_argument('--det_result_folder', default='det_results/', type=str)
parser.add_argument('--result_folder', default='summary_result/', type=str)
parser.add_argument('--summary_file', default='results.txt', type=str)
parser.add_argument('--output_name', default='output.mp4', type=str)
parser.add_argument('--perc', default=5, type=int)
parser.add_argument('--path_video', required=True, type=str)
args = parser.parse_args()
frame_list, frames = Utils_Video.extract_frames(args.path_video, args.perc)
det_frame_list,det_result_list=still_image_YOLO_DET(frame_list, frames, args.det_frames_folder,args.det_result_folder)
Utils_Video.make_video_from_list(args.output_name, det_frame_list)
print_YOLO_DET_result(det_result_list,args.result_folder, args.summary_file)
end = time.time()
print("Elapsed Time:%d Seconds"%(end-start))
print("Running Completed with Success!!!")
def main():
'''
Parse command line arguments and execute the code
'''
######### TENSORBOX PARAMETERS
start = time.time()
parser = argparse.ArgumentParser()
# parser.add_argument('--result_folder', default='summary_result/', type=str)
# parser.add_argument('--summary_file', default='results.txt', type=str)
parser.add_argument('--output_name', default='output.mp4', type=str)
parser.add_argument('--hypes',
default='./TENSORBOX/hypes/overfeat_rezoom.json',
type=str)
parser.add_argument('--weights',
default='./TENSORBOX/data/save.ckpt-1090000',
type=str)
parser.add_argument('--perc', default=2, type=int)
parser.add_argument('--path_video', required=True, type=str)
args = parser.parse_args()
# hypes_file = './hypes/overfeat_rezoom.json'
# weights_file= './output/save.ckpt-1090000'
path_video_folder = os.path.splitext(os.path.basename(args.path_video))[0]
pred_idl = './%s/%s_val.idl' % (path_video_folder, path_video_folder)
idl_filename = path_video_folder + '/' + path_video_folder + '.idl'
frame_list = []
frame_list = Utils_Video.extract_idl_from_frames(args.path_video,
args.perc,
path_video_folder,
'frames/', idl_filename)
progress = progressbar.ProgressBar(widgets=[
progressbar.Bar('=', '[', ']'), ' ',
progressbar.Percentage(), ' ',
progressbar.ETA()
])
for image_path in progress(frame_list):
Utils_Image.resizeImage(image_path)
Utils_Image.resizeImage(-1)
det_frame_list = Utils_Tensorbox.still_image_TENSORBOX_singleclass(
frame_list, path_video_folder, args.hypes, args.weights, pred_idl)
Utils_Video.make_video_from_list(args.output_name, det_frame_list)
end = time.time()
print("Elapsed Time:%d Seconds" % (end - start))
print("Running Completed with Success!!!")
def main():
'''
Parse command line arguments and execute the code
'''
######### TENSORBOX PARAMETERS
start = time.time()
parser = argparse.ArgumentParser()
parser.add_argument('--det_frames_folder', default='det_frames/', type=str)
parser.add_argument('--det_result_folder', default='det_results/', type=str)
parser.add_argument('--frames_folder', default='frames/', type=str)
# parser.add_argument('--result_folder', default='summary_result/', type=str)
# parser.add_argument('--summary_file', default='results.txt', type=str)
parser.add_argument('--output_name', default='output.mp4', type=str)
parser.add_argument('--hypes', default='./TENSORBOX/hypes/overfeat_rezoom.json', type=str)
parser.add_argument('--weights', default='./TENSORBOX/output/save.ckpt-1090000', type=str)
parser.add_argument('--perc', default=2, type=int)
parser.add_argument('--path_video', required=True, type=str)
args = parser.parse_args()
# hypes_file = './hypes/overfeat_rezoom.json'
# weights_file= './output/save.ckpt-1090000'
path_video_folder = os.path.splitext(os.path.basename(args.path_video))[0]
pred_idl = './%s/%s_val.idl' % (path_video_folder, path_video_folder)
idl_filename=path_video_folder+'/'+path_video_folder+'.idl'
frame_list=[]
frame_list = Utils_Video.extract_idl_from_frames(args.path_video, args.perc, path_video_folder, args.frames_folder, idl_filename )
progress = progressbar.ProgressBar(widgets=[progressbar.Bar('=', '[', ']'), ' ',progressbar.Percentage(), ' ',progressbar.ETA()])
for image_path in progress(frame_list):
Utils_Image.resizeImage(image_path)
det_frame_list=still_image_TENSORBOX(idl_filename, frame_list, args.det_frames_folder, args.det_result_folder, args.frames_folder, path_video_folder, args.hypes, args.weights, pred_idl)
Utils_Video.make_video_from_list(args.output_name, det_frame_list)
end = time.time()
print("Elapsed Time:%d Seconds"%(end-start))
print("Running Completed with Success!!!")
def main():
'''
Parse command line arguments and execute the code
'''
######### TENSORBOX PARAMETERS
start = time.time()
parser = argparse.ArgumentParser()
# parser.add_argument('--result_folder', default='summary_result/', type=str)
# parser.add_argument('--summary_file', default='results.txt', type=str)
parser.add_argument('--output_name', default='output.mp4', type=str)
parser.add_argument('--hypes',
default='./TENSORBOX/hypes/overfeat_rezoom.json',
type=str)
parser.add_argument('--weights',
default='./TENSORBOX/data/save.ckpt-1250000',
type=str)
parser.add_argument('--perc', default=100, type=int)
parser.add_argument('--path_video',
default='DAVIS-2017-TrainVal.mp4',
type=str) # required=True, type=str)
args = parser.parse_args()
# hypes_file = './hypes/overfeat_rezoom.json'
# weights_file= './output/save.ckpt-1090000'
path_video_folder = os.path.splitext(os.path.basename(args.path_video))[0]
pred_idl = './%s/%s_val.idl' % (path_video_folder, path_video_folder)
idl_filename = path_video_folder + '/' + path_video_folder + '.idl'
frame_tensorbox = []
frame_inception = []
frame_tensorbox, frame_inception = Utils_Video.extract_frames_incten(
args.path_video, args.perc, path_video_folder, idl_filename)
progress = progressbar.ProgressBar(widgets=[
progressbar.Bar('=', '[', ']'), ' ',
progressbar.Percentage(), ' ',
progressbar.ETA()
])
for image_path in progress(frame_tensorbox):
Utils_Image.resizeImage(image_path)
Utils_Image.resizeImage(-1)
video_info = Utils_Tensorbox.bbox_det_TENSORBOX_multiclass(
frame_tensorbox, path_video_folder, args.hypes, args.weights, pred_idl)
tracked_video = Utils_Video.recurrent_track_objects(video_info)
# tracked_video=utils_video.track_objects(video_info)
# labeled_video=Utils_Imagenet.label_video(tracked_video, frame_inception)
labeled_video = Utils_Imagenet.recurrent_label_video(
tracked_video, frame_inception)
# tracked_video=utils_video.track_objects(video_info)
# tracked_video=utils_video.track_and_label_objects(video_info)
labeled_frames = Utils_Video.draw_rectangles(path_video_folder,
labeled_video)
Utils_Video.make_tracked_video(args.output_name, labeled_frames)
frame.saveVideoResults(idl_filename, labeled_video)
# utils_video.make_tracked_video(args.output_name, labeled_video)
end = time.time()
print("Elapsed Time:%d Seconds" % (end - start))
print("Running Completed with Success!!!")