def handlePuzzle(imageFilename, vectorSet):
print >>sys.stderr, "Loading %s" % imageFilename
digits = mytry.processImage(imageFilename, interactive=False)
labels = mytry.readLabels(imageFilename + ".labels")
for ((i,j), im) in digits:
label = labels[j][i]
if label == ' ':
print >>sys.stderr, "Warning, cell (%d,%d) not empty but labeled as such" % (i,j)
continue
vectorSet.append((label, list((convert.cvImg2np(im)/255).flat)))
def main():
if len(sys.argv) != 3:
sys.stderr.write("Usage: %s trainingSet puzzle\n" % sys.argv[0])
sys.exit(1)
classifier = KNNClassifier(sys.argv[1])
digits = mytry.processImage(sys.argv[2], interactive=False)
res = [[' ' for i in range(9)] for j in range(9)]
for ((i,j), im) in digits:
# convert to same format as used in extractFeatures
# TODO: this should already be returned from processImage
im = list((convert.cvImg2np(im)/255).flat)
label = classifier.classify(im)
res[j][i] = label
for j, line in enumerate(res):
if j > 0 and j % 3 == 0:
sys.stdout.write("------+------+------\n")
for i, label in enumerate(line):
if i > 0 and i % 3 == 0:
sys.stdout.write("|")
sys.stdout.write(" " + label)
sys.stdout.write("\n")
