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Code Packages Releases Wiki Activity

support flownet2 with arbitary input size

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revise default proto to match the filename in documentations

fix a bug

beautify python codes

fix bug

beautify codes

add test samples with larger/smaller size

remove unless code

using bytearray without creating tmp file

remove useless codes
This commit is contained in:
zhaoyue-zephyrus
2020-07-22 23:07:17 +08:00
parent fe9ff64d64
commit e231be86b7
3 changed files with 41 additions and 15 deletions
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samples/dnn/optical_flow.py
+24 -6
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@@ -5,7 +5,7 @@ Original paper: https://arxiv.org/abs/1612.01925.
Original repo: https://github.com/lmb-freiburg/flownet2.
Download the converted .caffemodel model from https://drive.google.com/open?id=16qvE9VNmU39NttpZwZs81Ga8VYQJDaWZ
and .prototxt from https://drive.google.com/open?id=19bo6SWU2p8ZKvjXqMKiCPdK8mghwDy9b.
and .prototxt from https://drive.google.com/file/d/1RyNIUsan1ZOh2hpYIH36A-jofAvJlT6a/view?usp=sharing.
Otherwise download original model from https://lmb.informatik.uni-freiburg.de/resources/binaries/flownet2/flownet2-models.tar.gz,
convert .h5 model to .caffemodel and modify original .prototxt using .prototxt from link above.
'''
@@ -18,7 +18,7 @@ import cv2 as cv
class OpticalFlow(object):
def __init__(self, proto, model, height, width):
self.net = cv.dnn.readNet(proto, model)
self.net = cv.dnn.readNetFromCaffe(proto, model)
self.net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
self.height = height
self.width = width
@@ -62,9 +62,9 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Use this script to calculate optical flow using FlowNetv2',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-input', '-i', required=True, help='Path to input video file. Skip this argument to capture frames from a camera.')
parser.add_argument('--height', default=320, help='Input height')
parser.add_argument('--width', default=448, help='Input width')
parser.add_argument('--proto', '-p', default='FlowNet2_deploy.prototxt', help='Path to prototxt.')
parser.add_argument('--height', default=320, type=int, help='Input height')
parser.add_argument('--width', default=448, type=int, help='Input width')
parser.add_argument('--proto', '-p', default='FlowNet2_deploy_anysize.prototxt', help='Path to prototxt.')
parser.add_argument('--model', '-m', default='FlowNet2_weights.caffemodel', help='Path to caffemodel.')
args, _ = parser.parse_known_args()
@@ -75,7 +75,25 @@ if __name__ == '__main__':
cv.namedWindow(winName, cv.WINDOW_NORMAL)
cap = cv.VideoCapture(args.input if args.input else 0)
hasFrame, first_frame = cap.read()
opt_flow = OpticalFlow(args.proto, args.model, args.height, args.width)
divisor = 64.
var = {}
var['ADAPTED_WIDTH'] = int(np.ceil(args.width/divisor) * divisor)
var['ADAPTED_HEIGHT'] = int(np.ceil(args.height/divisor) * divisor)
var['SCALE_WIDTH'] = args.width / float(var['ADAPTED_WIDTH'])
var['SCALE_HEIGHT'] = args.height / float(var['ADAPTED_HEIGHT'])
config = ''
proto = open(args.proto).readlines()
for line in proto:
for key, value in var.items():
tag = "$%s$" % key
line = line.replace(tag, str(value))
config += line
caffemodel = open(args.model, 'rb').read()
opt_flow = OpticalFlow(bytearray(config.encode()), caffemodel, var['ADAPTED_HEIGHT'], var['ADAPTED_WIDTH'])
while cv.waitKey(1) < 0:
hasFrame, second_frame = cap.read()
if not hasFrame: