Mercurial Hosting > traffic-intelligence
diff python/cvutils.py @ 893:ff92801e5c54
updated hog to scikit-image 0.13 (needed to add a block_norm attribute in classifier.cfg)
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Tue, 30 May 2017 16:10:18 -0400 |
| parents | 1fdafa9f6bf4 |
| children | 0c1fed9e8862 |
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--- a/python/cvutils.py Fri May 05 00:07:33 2017 -0400 +++ b/python/cvutils.py Tue May 30 16:10:18 2017 -0400 @@ -605,10 +605,10 @@ from skimage.feature import hog from skimage import color, transform - def HOG(image, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8, 8), cellsPerBlock=(2, 2), visualize=False, normalize=False): + def HOG(image, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8,8), cellsPerBlock=(2,2), blockNorm='L1', visualize=False, normalize=False): bwImg = color.rgb2gray(image) inputImg = transform.resize(bwImg, rescaleSize) - features = hog(inputImg, orientations, pixelsPerCell, cellsPerBlock, visualize, normalize) + features = hog(inputImg, orientations, pixelsPerCell, cellsPerBlock, blockNorm, visualize, normalize) if visualize: from matplotlib.pyplot import imshow, figure, subplot hogViz = features[1] @@ -620,11 +620,11 @@ imshow(hogViz) return float32(features) - def createHOGTrainingSet(imageDirectory, classLabel, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8, 8), cellsPerBlock=(2, 2), visualize=False, normalize=False): + def createHOGTrainingSet(imageDirectory, classLabel, rescaleSize = (64,64), orientations=9, pixelsPerCell=(8,8), blockNorm='L1', cellsPerBlock=(2, 2), visualize=False, normalize=False): inputData = [] for filename in listdir(imageDirectory): img = imread(imageDirectory+filename) - features = HOG(img, rescaleSize, orientations, pixelsPerCell, cellsPerBlock, visualize, normalize) + features = HOG(img, rescaleSize, orientations, pixelsPerCell, cellsPerBlock, blockNorm, visualize, normalize) inputData.append(features) nImages = len(inputData)