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Visualise LoDE #2

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f19e8ae
Update perception_pipeline.py
Oct 22, 2022
15d24fd
Update container.py
Oct 22, 2022
d53b1a3
Update perception_pipeline.py
Oct 24, 2022
2e77994
Update container.py
Oct 24, 2022
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27 changes: 23 additions & 4 deletions libs/perception/container.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
# Authors:
# - Yik Lung Pang: y.l.pang@qmul.ac.uk
# - Alessio Xompero: a.xompero@qmul.ac.uk
#
# - Tommaso Apicella: t.apicella@qmul.ac.uk
# MIT License

# Copyright (c) 2021 CORSMAL
Expand Down Expand Up @@ -219,6 +219,7 @@ def __init__(self, args, ncams):

self.zt1 = None
self.zt = None
self.visualise_LoDE = args.visualise_LoDE



Expand Down Expand Up @@ -301,7 +302,7 @@ def computeAnglesRad(self):

self.anglesrad = anglesrad

def ShapeFitting(self, _c1, _c2, _objmask1, _objmask2, h_step, r_step):
def ShapeFitting(self, _c1, _c2, _objmask1, _objmask2, h_step, r_step, rgb1, rgb2):

c1 = copy.deepcopy(_c1)
c2 = copy.deepcopy(_c2)
Expand Down Expand Up @@ -382,7 +383,19 @@ def ShapeFitting(self, _c1, _c2, _objmask1, _objmask2, h_step, r_step):

if (np.count_nonzero(areIn_c1) == areIn_c1.shape[0]) and (np.count_nonzero(areIn_c2) == areIn_c2.shape[0]):
converged_circ = True
break
if self.visualise_LoDE:
for p, isIn in zip(p2d_c1, areIn_c1):
if isIn:
cv2.circle(rgb1, (int(p[0]), int(p[1])), 2, (255, 0, 0), -1)
else:
cv2.circle(rgb1, (int(p[0]), int(p[1])), 2, (0, 0, 255), -1)

for p, isIn in zip(p2d_c2, areIn_c2):
if isIn:
cv2.circle(rgb2, (int(p[0]), int(p[1])), 2, (255, 0, 0), -1)
else:
cv2.circle(rgb2, (int(p[0]), int(p[1])), 2, (0, 0, 255), -1)
break

if rad==minDiameter/2:
break
Expand All @@ -400,6 +413,12 @@ def ShapeFitting(self, _c1, _c2, _objmask1, _objmask2, h_step, r_step):
self.estRadius = convRadius[round(0.1*len(convRadius)):round(0.9*len(convRadius))]
self.estHeights = convHeights[round(0.1*len(convHeights)):round(0.9*len(convHeights))]

if self.visualise_LoDE:
dim = (rgb1.shape[1] // 2, rgb2.shape[0] // 2)
cv2.imshow("LoDE [blue] and object mask [green]", np.hstack([cv2.resize(rgb1, dim, interpolation=cv2.INTER_AREA),
cv2.resize(rgb2, dim, interpolation=cv2.INTER_AREA)]))
cv2.waitKey(10)


# Localisation and dimension estimation via shape reconstruction in 3D
# Output:
Expand Down Expand Up @@ -462,7 +481,7 @@ def LoDE(self, rgb1, rgb2, c1, c2, instances1, instances2, h_step, r_step):
objmask2 = np.uint8(255.* (instances2['masks'][j] >= 0.5))

# print('ShapeFitting')
self.ShapeFitting(c1, c2, objmask1, objmask2, h_step, r_step)
self.ShapeFitting(c1, c2, objmask1, objmask2, h_step, r_step, rgb1, rgb2)

# print('ComputeDimensions')
# Compute container dimensions
Expand Down
4 changes: 3 additions & 1 deletion perception_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,11 +4,12 @@
# Author: Ricardo Sanchez Matilla
# Author: Yik Lung Pang
# Author: Alessio Xompero
# Author: Tommaso Apicella
# Email: corsmal-benchmark@qmul.ac.uk
#
#
# Created Date: 2020/02/13
# Modified Date: 2020/10/05
# Modified Date: 2022/10/24
#
# Centre for Intelligent Sensing, Queen Mary University of London, UK
#
Expand Down Expand Up @@ -137,6 +138,7 @@ def PublicTestingDataParser(args):
parser.add_argument('--use_LoDE', type=int, choices=[0,1], default=0)
parser.add_argument('--LoDE_hstep', type=float, default=0.001)
parser.add_argument('--LoDE_rstep', type=float, default=18.0)
parser.add_argument('--visualise_LoDE', type=bool, default=False)
parser.add_argument('--record', type=int, choices=[0,1], default=0)
parser.add_argument('--max_num_frames', type=int, default=-1)
# Path to videos
Expand Down