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dat/yolo/yolov3-tiny.weights filter=lfs diff=lfs merge=lfs -text | ||
dat/yolo/yolov3.weights filter=lfs diff=lfs merge=lfs -text |
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cmake_minimum_required(VERSION 2.8 FATAL_ERROR) | ||
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add_definitions(-std=c++11) | ||
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set(CXX_FLAGS "-Wall") | ||
set(CMAKE_CXX_FLAGS, "${CXX_FLAGS}") | ||
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project(camera_fusion) | ||
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find_package(OpenCV 4.1 REQUIRED) | ||
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include_directories(${OpenCV_INCLUDE_DIRS}) | ||
link_directories(${OpenCV_LIBRARY_DIRS}) | ||
add_definitions(${OpenCV_DEFINITIONS}) | ||
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# Executable for create matrix exercise | ||
add_executable (3D_object_tracking src/camFusion_Student.cpp src/FinalProject_Camera.cpp src/lidarData.cpp src/matching2D_Student.cpp src/objectDetection2D.cpp) | ||
target_link_libraries (3D_object_tracking ${OpenCV_LIBRARIES}) |
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person | ||
bicycle | ||
car | ||
motorbike | ||
aeroplane | ||
bus | ||
train | ||
truck | ||
boat | ||
traffic light | ||
fire hydrant | ||
stop sign | ||
parking meter | ||
bench | ||
bird | ||
cat | ||
dog | ||
horse | ||
sheep | ||
cow | ||
elephant | ||
bear | ||
zebra | ||
giraffe | ||
backpack | ||
umbrella | ||
handbag | ||
tie | ||
suitcase | ||
frisbee | ||
skis | ||
snowboard | ||
sports ball | ||
kite | ||
baseball bat | ||
baseball glove | ||
skateboard | ||
surfboard | ||
tennis racket | ||
bottle | ||
wine glass | ||
cup | ||
fork | ||
knife | ||
spoon | ||
bowl | ||
banana | ||
apple | ||
sandwich | ||
orange | ||
broccoli | ||
carrot | ||
hot dog | ||
pizza | ||
donut | ||
cake | ||
chair | ||
sofa | ||
pottedplant | ||
bed | ||
diningtable | ||
toilet | ||
tvmonitor | ||
laptop | ||
mouse | ||
remote | ||
keyboard | ||
cell phone | ||
microwave | ||
oven | ||
toaster | ||
sink | ||
refrigerator | ||
book | ||
clock | ||
vase | ||
scissors | ||
teddy bear | ||
hair drier | ||
toothbrush |
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[net] | ||
# Testing | ||
batch=1 | ||
subdivisions=1 | ||
# Training | ||
# batch=64 | ||
# subdivisions=2 | ||
width=416 | ||
height=416 | ||
channels=3 | ||
momentum=0.9 | ||
decay=0.0005 | ||
angle=0 | ||
saturation = 1.5 | ||
exposure = 1.5 | ||
hue=.1 | ||
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learning_rate=0.001 | ||
burn_in=1000 | ||
max_batches = 500200 | ||
policy=steps | ||
steps=400000,450000 | ||
scales=.1,.1 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=16 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=2 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=32 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=2 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=64 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=2 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=128 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=2 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=256 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=2 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=512 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[maxpool] | ||
size=2 | ||
stride=1 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=1024 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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########### | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=256 | ||
size=1 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=512 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[convolutional] | ||
size=1 | ||
stride=1 | ||
pad=1 | ||
filters=255 | ||
activation=linear | ||
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[yolo] | ||
mask = 3,4,5 | ||
anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
classes=80 | ||
num=6 | ||
jitter=.3 | ||
ignore_thresh = .7 | ||
truth_thresh = 1 | ||
random=1 | ||
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[route] | ||
layers = -4 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=128 | ||
size=1 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[upsample] | ||
stride=2 | ||
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[route] | ||
layers = -1, 8 | ||
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[convolutional] | ||
batch_normalize=1 | ||
filters=256 | ||
size=3 | ||
stride=1 | ||
pad=1 | ||
activation=leaky | ||
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[convolutional] | ||
size=1 | ||
stride=1 | ||
pad=1 | ||
filters=255 | ||
activation=linear | ||
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[yolo] | ||
mask = 0,1,2 | ||
anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | ||
classes=80 | ||
num=6 | ||
jitter=.3 | ||
ignore_thresh = .7 | ||
truth_thresh = 1 | ||
random=1 |
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