Mercurial Hosting > traffic-intelligence
changeset 1243:88eedf79f16a
correct classifier.cfg and info classification
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
---|---|
date | Wed, 07 Feb 2024 11:53:00 -0500 |
parents | 4cd8ace3552f |
children | 00b71da2baac |
files | classifier.cfg scripts/classify-objects.py |
diffstat | 2 files changed, 5 insertions(+), 1 deletions(-) [+] |
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--- a/classifier.cfg Wed Feb 07 11:43:03 2024 -0500 +++ b/classifier.cfg Wed Feb 07 11:53:00 2024 -0500 @@ -3,7 +3,8 @@ # filename of the cyc/veh SVM classifier bv-svm-filename = modelBV.xml # filename of a Ultralytics-compatible model, eg Yolov8 -dl-filename = +# if the filename is valid, it will be used, otherwise the SVMs +dl-filename = yolov8x.pt # percent increase of the max of width and height of the bounding box of features extracted for classification percent-increase-crop = 0.2 # min number of pixels in cropped image to classify by SVM @@ -18,6 +19,8 @@ hog-ncells-block = 2 # block normalization method (L1, L1-sqrt, L2, L2-Hys) hog-block-norm = L1-sqrt +# object confidence threshold for detection +confidence = 0.25 # method to aggregate road user speed: mean, median or any (per)centile speed-aggregation-method = median # number of frames to ignore at both ends of a series (noisy)
--- a/scripts/classify-objects.py Wed Feb 07 11:43:03 2024 -0500 +++ b/scripts/classify-objects.py Wed Feb 07 11:53:00 2024 -0500 @@ -43,6 +43,7 @@ bikeCarSVM = None yolo = YOLO(classifierParams.dlFilename, task='detect') useYolo = True + print('Using Yolov8 model +'classifierParams.dlFilename) else: useYolo = False pedBikeCarSVM = ml.SVM_load(classifierParams.pedBikeCarSVMFilename)