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name_15 |
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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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[detection] | ||
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#----------------------------- | ||
# opencv_dnn = 12 | ||
# darknet_cudnn = 10 | ||
# tensorrt = 11 | ||
detector_backend = 12 | ||
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#----------------------------- | ||
# Target and backend for opencv_dnn detector | ||
# DNN_TARGET_CPU | ||
# DNN_TARGET_OPENCL | ||
# DNN_TARGET_OPENCL_FP16 | ||
# DNN_TARGET_MYRIAD | ||
# DNN_TARGET_CUDA | ||
# DNN_TARGET_CUDA_FP16 | ||
ocv_dnn_target = DNN_TARGET_CPU | ||
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||
# DNN_BACKEND_DEFAULT | ||
# DNN_BACKEND_HALIDE | ||
# DNN_BACKEND_INFERENCE_ENGINE | ||
# DNN_BACKEND_OPENCV | ||
# DNN_BACKEND_VKCOM | ||
# DNN_BACKEND_CUDA | ||
# DNN_BACKEND_INFERENCE_ENGINE_NGRAPH | ||
# DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 | ||
ocv_dnn_backend = DNN_BACKEND_OPENCV | ||
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#----------------------------- | ||
nn_weights = C:/work/home/mtracker/Multitarget-tracker/data/coco/yolov10s.onnx | ||
nn_config = C:/work/home/mtracker/Multitarget-tracker/data/coco/yolov10s.onnx | ||
class_names = C:/work/home/mtracker/Multitarget-tracker/data/coco/coco.names | ||
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#----------------------------- | ||
confidence_threshold = 0.3 | ||
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max_crop_ratio = 0 | ||
max_batch = 1 | ||
gpu_id = 0 | ||
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#----------------------------- | ||
# YOLOV3 | ||
# YOLOV4 | ||
# YOLOV5 | ||
net_type = YOLOV10 | ||
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#----------------------------- | ||
# INT8 | ||
# FP16 | ||
# FP32 | ||
inference_precision = FP16 | ||
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[tracking] | ||
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#----------------------------- | ||
# DistCenters = 0 // Euclidean distance between centers, pixels | ||
# DistRects = 1 // Euclidean distance between bounding rectangles, pixels | ||
# DistJaccard = 2 // Intersection over Union, IoU, [0, 1] | ||
# DistHist = 3 // Bhatacharia distance between histograms, [0, 1] | ||
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distance_type = 0 | ||
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#----------------------------- | ||
# KalmanLinear = 0 | ||
# KalmanUnscented = 1 | ||
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kalman_type = 0 | ||
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#----------------------------- | ||
# FilterCenter = 0 | ||
# FilterRect = 1 | ||
# FilterRRect = 2 | ||
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filter_goal = 0 | ||
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#----------------------------- | ||
# TrackNone = 0 | ||
# TrackKCF = 1 | ||
# TrackMIL = 2 | ||
# TrackMedianFlow = 3 | ||
# TrackGOTURN = 4 | ||
# TrackMOSSE = 5 | ||
# TrackCSRT = 6 | ||
# TrackDAT = 7 | ||
# TrackSTAPLE = 8 | ||
# TrackLDES = 9 | ||
# TrackDaSiamRPN = 10 | ||
# Used if filter_goal == FilterRect | ||
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lost_track_type = 0 | ||
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#----------------------------- | ||
# MatchHungrian = 0 | ||
# MatchBipart = 1 | ||
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match_type = 0 | ||
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#----------------------------- | ||
# Use constant acceleration motion model: | ||
# 0 - unused (stable) | ||
# 1 - use acceleration in Kalman filter (experimental) | ||
use_aceleration = 0 | ||
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#----------------------------- | ||
# Delta time for Kalman filter | ||
delta_time = 0.4 | ||
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#----------------------------- | ||
# Accel noise magnitude for Kalman filter | ||
accel_noise = 0.2 | ||
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#----------------------------- | ||
# Distance threshold between region and object on two frames | ||
dist_thresh = 0.8 | ||
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#----------------------------- | ||
# If this value > 0 than will be used circle with this radius | ||
# If this value <= 0 than will be used ellipse with size (3*vx, 3*vy), vx and vy - horizontal and vertical speed in pixelsa | ||
min_area_radius_pix = -1 | ||
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#----------------------------- | ||
# Minimal area radius in ration for object size. Used if min_area_radius_pix < 0 | ||
min_area_radius_k = 0.8 | ||
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#----------------------------- | ||
# If the object do not assignment more than this frames then it will be removed | ||
max_skip_frames = 50 | ||
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#----------------------------- | ||
# The maximum trajectory length | ||
max_trace_len = 50 | ||
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#----------------------------- | ||
# Detection abandoned objects | ||
detect_abandoned = 0 | ||
# After this time (in seconds) the object is considered abandoned | ||
min_static_time = 5 | ||
# After this time (in seconds) the abandoned object will be removed | ||
max_static_time = 25 | ||
# Speed in pixels. If speed of object is more that this value than object is non static | ||
max_speed_for_static = 10 |
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,142 @@ | ||
[detection] | ||
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||
#----------------------------- | ||
# opencv_dnn = 12 | ||
# darknet_cudnn = 10 | ||
# tensorrt = 11 | ||
detector_backend = 11 | ||
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||
#----------------------------- | ||
# Target and backend for opencv_dnn detector | ||
# DNN_TARGET_CPU | ||
# DNN_TARGET_OPENCL | ||
# DNN_TARGET_OPENCL_FP16 | ||
# DNN_TARGET_MYRIAD | ||
# DNN_TARGET_CUDA | ||
# DNN_TARGET_CUDA_FP16 | ||
ocv_dnn_target = DNN_TARGET_CPU | ||
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||
# DNN_BACKEND_DEFAULT | ||
# DNN_BACKEND_HALIDE | ||
# DNN_BACKEND_INFERENCE_ENGINE | ||
# DNN_BACKEND_OPENCV | ||
# DNN_BACKEND_VKCOM | ||
# DNN_BACKEND_CUDA | ||
# DNN_BACKEND_INFERENCE_ENGINE_NGRAPH | ||
# DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 | ||
ocv_dnn_backend = DNN_BACKEND_OPENCV | ||
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||
#----------------------------- | ||
nn_weights = C:/work/home/mtracker/Multitarget-tracker/data/yolov8s-obb.onnx | ||
nn_config = C:/work/home/mtracker/Multitarget-tracker/data/yolov8s-obb.onnx | ||
class_names = C:/work/home/mtracker/Multitarget-tracker/data/DOTA.names | ||
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#----------------------------- | ||
confidence_threshold = 0.5 | ||
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||
max_crop_ratio = 0 | ||
max_batch = 1 | ||
gpu_id = 0 | ||
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||
#----------------------------- | ||
# YOLOV3 | ||
# YOLOV4 | ||
# YOLOV5 | ||
net_type = YOLOV8_OBB | ||
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||
#----------------------------- | ||
# INT8 | ||
# FP16 | ||
# FP32 | ||
inference_precision = FP16 | ||
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||
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||
[tracking] | ||
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||
#----------------------------- | ||
# DistCenters = 0 // Euclidean distance between centers, pixels | ||
# DistRects = 1 // Euclidean distance between bounding rectangles, pixels | ||
# DistJaccard = 2 // Intersection over Union, IoU, [0, 1] | ||
# DistHist = 3 // Bhatacharia distance between histograms, [0, 1] | ||
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||
distance_type = 0 | ||
|
||
#----------------------------- | ||
# KalmanLinear = 0 | ||
# KalmanUnscented = 1 | ||
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||
kalman_type = 0 | ||
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||
#----------------------------- | ||
# FilterCenter = 0 | ||
# FilterRect = 1 | ||
# FilterRRect = 2 | ||
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||
filter_goal = 0 | ||
|
||
#----------------------------- | ||
# TrackNone = 0 | ||
# TrackKCF = 1 | ||
# TrackMIL = 2 | ||
# TrackMedianFlow = 3 | ||
# TrackGOTURN = 4 | ||
# TrackMOSSE = 5 | ||
# TrackCSRT = 6 | ||
# TrackDAT = 7 | ||
# TrackSTAPLE = 8 | ||
# TrackLDES = 9 | ||
# TrackDaSiamRPN = 10 | ||
# Used if filter_goal == FilterRect | ||
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||
lost_track_type = 0 | ||
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||
#----------------------------- | ||
# MatchHungrian = 0 | ||
# MatchBipart = 1 | ||
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||
match_type = 0 | ||
|
||
#----------------------------- | ||
# Use constant acceleration motion model: | ||
# 0 - unused (stable) | ||
# 1 - use acceleration in Kalman filter (experimental) | ||
use_aceleration = 0 | ||
|
||
#----------------------------- | ||
# Delta time for Kalman filter | ||
delta_time = 0.4 | ||
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||
#----------------------------- | ||
# Accel noise magnitude for Kalman filter | ||
accel_noise = 0.2 | ||
|
||
#----------------------------- | ||
# Distance threshold between region and object on two frames | ||
dist_thresh = 0.8 | ||
|
||
#----------------------------- | ||
# If this value > 0 than will be used circle with this radius | ||
# If this value <= 0 than will be used ellipse with size (3*vx, 3*vy), vx and vy - horizontal and vertical speed in pixelsa | ||
min_area_radius_pix = -1 | ||
|
||
#----------------------------- | ||
# Minimal area radius in ration for object size. Used if min_area_radius_pix < 0 | ||
min_area_radius_k = 0.8 | ||
|
||
#----------------------------- | ||
# If the object do not assignment more than this frames then it will be removed | ||
max_skip_frames = 50 | ||
|
||
#----------------------------- | ||
# The maximum trajectory length | ||
max_trace_len = 50 | ||
|
||
#----------------------------- | ||
# Detection abandoned objects | ||
detect_abandoned = 0 | ||
# After this time (in seconds) the object is considered abandoned | ||
min_static_time = 5 | ||
# After this time (in seconds) the abandoned object will be removed | ||
max_static_time = 25 | ||
# Speed in pixels. If speed of object is more that this value than object is non static | ||
max_speed_for_static = 10 |
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