import create_segments
import sys
import logging
### Own modules
from general.hog import doHog
from general.pca import runPCA
from general.create_sets import create_sets
from train.svm import runSVM
from train.knn import runKNN
segmentDir = 'tmp/segments/'
featureDir = 'tmp/features/'
trainDir = featureDir + 'train/'
testDir = featureDir + 'test/'
for k in range(19):
k += 1
avgAcc = 0.0
for i in range(10):
print "hog"
doHog(segmentDir, featureDir, "xeryus")
print "create sets"
create_sets(featureDir)
print "knn"
kNN, accuracy = runKNN(trainDir, testDir, k, "hog")
avgAcc += accuracy
print "Average accuracy for k =", k, ":\t", avgAcc/10
avgAcc = 0
import create_segments
import sys
import logging
### Own modules
from general.hog import doHog
from general.pca import runPCA
from general.create_sets import create_sets
from train.svm import runSVM
from train.knn import runKNN
segmentDir = 'tmp/segments/'
featureDir = 'tmp/features/'
trainDir = featureDir + 'train/'
testDir = featureDir + 'test/'
for k in range(19):
k += 1
avgAcc = 0.0
for i in range(10):
print "hog"
doHog(segmentDir, featureDir, "xeryus")
print "create sets"
create_sets(featureDir)
print "knn"
kNN, accuracy = runKNN(trainDir, testDir, k, "hog")
avgAcc += accuracy
print "Average accuracy for k =", k, ":\t", avgAcc / 10
avgAcc = 0
createSegments = False
if len(sys.argv) == 2:
createSegments = True
### Directories
segmentDir = 'tmp/segments/'
featureDir = 'tmp/features/'
trainDir = featureDir + 'train/'
### First segment the training images
if createSegments:
logging.info("Creating segments of the images")
create_segments.create_seg()
### Run hog over the segmented images
### Third argument for type of hog ("xeryus" or "other"), default = "xeryus"
logging.info("Doing the HOG")
doHog(segmentDir, featureDir)
### Create random train and test sets from the hog features
# logging.info("Creating train and test set")
create_sets(featureDir)
### Receive trained kNN (it also tests it on characters)
logging.info("Running kNN")
k = 10
kNN = runKNN(trainDir, k)
with open('tmp/knn.pickle', 'w') as f:
pickle.dump(kNN, f)
from train.svm import runSVM
import create_segments
if __name__ == '__main__':
if len(sys.argv) >= 2 and sys.argv[1] != "--create_segments":
print("Usage: python %s [--create_segments]" % sys.argv[0])
need_create_segments = len(sys.argv) == 2
segmentDir = Path('tmp/segments/')
featureDir = Path('tmp/features/')
trainDir = featureDir + 'train/'
testDir = featureDir + 'test/'
if need_create_segments:
logging.info("Create segments of the images")
create_segments.create_seg()
logging.info("Creating HOG features")
doHog(segmentDir, featureDir)
logging.info("Creating train and test set")
create_sets(featureDir, 0.7)
logging.info("Running SVM")
SVM, accuracy = runSVM(trainDir, testDir)
logging.info("SVM accuracy: %f" % accuracy)
with open('tmp/svm.pickle', 'w') as f:
pickle.dump(SVM, f)
logging.info("Done")