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Merge branch 4.x

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This commit is contained in:
Alexander Alekhin
2021-06-04 11:51:43 +00:00
parent b754406352 3e513ee6ab
commit b91e0dca90
253 changed files with 13923 additions and 3300 deletions
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samples/python/stitching_detailed.py
+12 -15
View File
@@ -49,8 +49,6 @@ except AttributeError:
print("AKAZE not available")
SEAM_FIND_CHOICES = OrderedDict()
SEAM_FIND_CHOICES['gc_color'] = cv.detail_GraphCutSeamFinder('COST_COLOR')
SEAM_FIND_CHOICES['gc_colorgrad'] = cv.detail_GraphCutSeamFinder('COST_COLOR_GRAD')
SEAM_FIND_CHOICES['dp_color'] = cv.detail_DpSeamFinder('COLOR')
SEAM_FIND_CHOICES['dp_colorgrad'] = cv.detail_DpSeamFinder('COLOR_GRAD')
SEAM_FIND_CHOICES['voronoi'] = cv.detail.SeamFinder_createDefault(cv.detail.SeamFinder_VORONOI_SEAM)
@@ -79,7 +77,10 @@ WARP_CHOICES = (
'transverseMercator',
)
WAVE_CORRECT_CHOICES = ('horiz', 'no', 'vert',)
WAVE_CORRECT_CHOICES = OrderedDict()
WAVE_CORRECT_CHOICES['horiz'] = cv.detail.WAVE_CORRECT_HORIZ
WAVE_CORRECT_CHOICES['no'] = None
WAVE_CORRECT_CHOICES['vert'] = cv.detail.WAVE_CORRECT_VERT
BLEND_CHOICES = ('multiband', 'feather', 'no',)
@@ -147,9 +148,9 @@ parser.add_argument(
type=str, dest='ba_refine_mask'
)
parser.add_argument(
'--wave_correct', action='store', default=WAVE_CORRECT_CHOICES[0],
help="Perform wave effect correction. The default is '%s'" % WAVE_CORRECT_CHOICES[0],
choices=WAVE_CORRECT_CHOICES,
'--wave_correct', action='store', default=list(WAVE_CORRECT_CHOICES.keys())[0],
help="Perform wave effect correction. The default is '%s'" % list(WAVE_CORRECT_CHOICES.keys())[0],
choices=WAVE_CORRECT_CHOICES.keys(),
type=str, dest='wave_correct'
)
parser.add_argument(
@@ -279,11 +280,7 @@ def main():
compose_megapix = args.compose_megapix
conf_thresh = args.conf_thresh
ba_refine_mask = args.ba_refine_mask
wave_correct = args.wave_correct
if wave_correct == 'no':
do_wave_correct = False
else:
do_wave_correct = True
wave_correct = WAVE_CORRECT_CHOICES[args.wave_correct]
if args.save_graph is None:
save_graph = False
else:
@@ -343,7 +340,7 @@ def main():
with open(args.save_graph, 'w') as fh:
fh.write(cv.detail.matchesGraphAsString(img_names, p, conf_thresh))
indices = cv.detail.leaveBiggestComponent(features, p, 0.3)
indices = cv.detail.leaveBiggestComponent(features, p, conf_thresh)
img_subset = []
img_names_subset = []
full_img_sizes_subset = []
@@ -393,11 +390,11 @@ def main():
warped_image_scale = focals[len(focals) // 2]
else:
warped_image_scale = (focals[len(focals) // 2] + focals[len(focals) // 2 - 1]) / 2
if do_wave_correct:
if wave_correct is not None:
rmats = []
for cam in cameras:
rmats.append(np.copy(cam.R))
rmats = cv.detail.waveCorrect(rmats, cv.detail.WAVE_CORRECT_HORIZ)
rmats = cv.detail.waveCorrect(rmats, wave_correct)
for idx, cam in enumerate(cameras):
cam.R = rmats[idx]
corners = []
@@ -433,7 +430,7 @@ def main():
compensator.feed(corners=corners, images=images_warped, masks=masks_warped)
seam_finder = SEAM_FIND_CHOICES[args.seam]
seam_finder.find(images_warped_f, corners, masks_warped)
masks_warped = seam_finder.find(images_warped_f, corners, masks_warped)
compose_scale = 1
corners = []
sizes = []
samples/python/tracker.py
+59 -6
View File
@@ -3,8 +3,22 @@
'''
Tracker demo
For usage download models by following links
For GOTURN:
goturn.prototxt and goturn.caffemodel: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking
For DaSiamRPN:
network: https://www.dropbox.com/s/rr1lk9355vzolqv/dasiamrpn_model.onnx?dl=0
kernel_r1: https://www.dropbox.com/s/999cqx5zrfi7w4p/dasiamrpn_kernel_r1.onnx?dl=0
kernel_cls1: https://www.dropbox.com/s/qvmtszx5h339a0w/dasiamrpn_kernel_cls1.onnx?dl=0
USAGE:
tracker.py [<video_source>]
tracker.py [-h] [--input INPUT] [--tracker_algo TRACKER_ALGO]
[--goturn GOTURN] [--goturn_model GOTURN_MODEL]
[--dasiamrpn_net DASIAMRPN_NET]
[--dasiamrpn_kernel_r1 DASIAMRPN_KERNEL_R1]
[--dasiamrpn_kernel_cls1 DASIAMRPN_KERNEL_CLS1]
[--dasiamrpn_backend DASIAMRPN_BACKEND]
[--dasiamrpn_target DASIAMRPN_TARGET]
'''
# Python 2/3 compatibility
@@ -14,18 +28,37 @@ import sys
import numpy as np
import cv2 as cv
import argparse
from video import create_capture, presets
class App(object):
def initializeTracker(self, image):
def __init__(self, args):
self.args = args
def initializeTracker(self, image, trackerAlgorithm):
while True:
if trackerAlgorithm == 'mil':
tracker = cv.TrackerMIL_create()
elif trackerAlgorithm == 'goturn':
params = cv.TrackerGOTURN_Params()
params.modelTxt = self.args.goturn
params.modelBin = self.args.goturn_model
tracker = cv.TrackerGOTURN_create(params)
elif trackerAlgorithm == 'dasiamrpn':
params = cv.TrackerDaSiamRPN_Params()
params.model = self.args.dasiamrpn_net
params.kernel_cls1 = self.args.dasiamrpn_kernel_cls1
params.kernel_r1 = self.args.dasiamrpn_kernel_r1
tracker = cv.TrackerDaSiamRPN_create(params)
else:
sys.exit("Tracker {} is not recognized. Please use one of three available: mil, goturn, dasiamrpn.".format(trackerAlgorithm))
print('==> Select object ROI for tracker ...')
bbox = cv.selectROI('tracking', image)
print('ROI: {}'.format(bbox))
tracker = cv.TrackerMIL_create()
try:
tracker.init(image, bbox)
except Exception as e:
@@ -37,7 +70,8 @@ class App(object):
return tracker
def run(self):
videoPath = sys.argv[1] if len(sys.argv) >= 2 else 'vtest.avi'
videoPath = self.args.input
trackerAlgorithm = self.args.tracker_algo
camera = create_capture(videoPath, presets['cube'])
if not camera.isOpened():
sys.exit("Can't open video stream: {}".format(videoPath))
@@ -48,7 +82,7 @@ class App(object):
assert image is not None
cv.namedWindow('tracking')
tracker = self.initializeTracker(image)
tracker = self.initializeTracker(image, trackerAlgorithm)
print("==> Tracking is started. Press 'SPACE' to re-initialize tracker or 'ESC' for exit...")
@@ -76,5 +110,24 @@ class App(object):
if __name__ == '__main__':
print(__doc__)
App().run()
parser = argparse.ArgumentParser(description="Run tracker")
parser.add_argument("--input", type=str, default="vtest.avi", help="Path to video source")
parser.add_argument("--tracker_algo", type=str, default="mil", help="One of three available tracking algorithms: mil, goturn, dasiamrpn")
parser.add_argument("--goturn", type=str, default="goturn.prototxt", help="Path to GOTURN architecture")
parser.add_argument("--goturn_model", type=str, default="goturn.caffemodel", help="Path to GOTERN model")
parser.add_argument("--dasiamrpn_net", type=str, default="dasiamrpn_model.onnx", help="Path to onnx model of DaSiamRPN net")
parser.add_argument("--dasiamrpn_kernel_r1", type=str, default="dasiamrpn_kernel_r1.onnx", help="Path to onnx model of DaSiamRPN kernel_r1")
parser.add_argument("--dasiamrpn_kernel_cls1", type=str, default="dasiamrpn_kernel_cls1.onnx", help="Path to onnx model of DaSiamRPN kernel_cls1")
parser.add_argument("--dasiamrpn_backend", type=int, default=0, help="Choose one of computation backends:\
0: automatically (by default),\
1: Halide language (http://halide-lang.org/),\
2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit),\
3: OpenCV implementation")
parser.add_argument("--dasiamrpn_target", type=int, default=0, help="Choose one of target computation devices:\
0: CPU target (by default),\
1: OpenCL,\
2: OpenCL fp16 (half-float precision),\
3: VPU")
args = parser.parse_args()
App(args).run()
cv.destroyAllWindows()