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car-detection-bayes
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kmeans() cleanup

This commit is contained in:
Glenn Jocher 2020-05-02 09:20:19 -07:00
parent be87b41aa2
commit ee7cba65a5
1 changed files with 2 additions and 2 deletions
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4
utils/utils.py
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@ -690,7 +690,7 @@ def coco_single_class_labels(path='../coco/labels/train2014/', label_class=43):
shutil.copyfile(src=img_file, dst='new/images/' + Path(file).name.replace('txt', 'jpg')) # copy images
def kmean_anchors(path='../coco/train2017.txt', n=12, img_size=(320, 1024), thr=0.10, gen=1000):
def kmean_anchors(path='./data/coco64.txt', n=9, img_size=(320, 1024), thr=0.20, gen=1000):
# Creates kmeans anchors for use in *.cfg files: from utils.utils import *; _ = kmean_anchors()
# n: number of anchors
# img_size: (min, max) image size used for multi-scale training (can be same values)
@ -717,7 +717,7 @@ def kmean_anchors(path='../coco/train2017.txt', n=12, img_size=(320, 1024), thr=
# Get label wh
wh = []
dataset = LoadImagesAndLabels(path, augment=True, rect=True, cache_labels=True)
dataset = LoadImagesAndLabels(path, augment=True, rect=True)
nr = 1 if img_size[0] == img_size[1] else 10 # number augmentation repetitions
for s, l in zip(dataset.shapes, dataset.labels):
wh.append(l[:, 3:5] * (s / s.max())) # image normalized to letterbox normalized wh