# parse parameters
datasetDir = sys.argv[1]
assert os.path.isdir(
datasetDir), 'Error <datasetDir>=%s does not exist' % datasetDir
if len(sys.argv) > 2:
outputDir = sys.argv[2]
else:
# default
outputDir = os.path.join(datasetDir, 'results')
# path2data
testData_pathToCalib = os.path.join(datasetDir, 'testing/calib')
outputDir_perspective = os.path.join(outputDir,
'baseline_perspective_test')
outputDir_bev = os.path.join(outputDir, 'baseline_bev_test')
# Run computeBaseline script to generate example classification results on testing set
# Replace by your algorithm to generate real results
trainDir = os.path.join(datasetDir, 'training')
testDir = os.path.join(datasetDir, 'testing')
computeBaseline.main(trainDir, testDir, outputDir_perspective)
# Convert baseline in perspective space into BEV space
# If your algorithm provides results in perspective space,
# you need to run this script before submission!
inputFiles = os.path.join(outputDir_perspective, '*.png')
transform2BEV.main(inputFiles, testData_pathToCalib, outputDir_bev)
# now zip the contents in the directory 'outputDir_bev' and upload
# the zip file to the KITTI server
datasetDir = sys.argv[1]
assert os.path.isdir(datasetDir), 'Error <datasetDir>=%s does not exist' %datasetDir
if len(sys.argv)>2:
outputDir = sys.argv[2]
else:
# default
outputDir = os.path.join(datasetDir, 'results')
# path2data
testData_pathToCalib = os.path.join(datasetDir, 'testing/calib')
outputDir_perspective = os.path.join(outputDir, 'baseline_perspective_test')
outputDir_bev = os.path.join(outputDir, 'baseline_bev_test')
# Run computeBaseline script to generate example classification results on testing set
# Replace by your algorithm to generate real results
trainDir = os.path.join(datasetDir, 'training')
testDir = os.path.join(datasetDir, 'testing')
computeBaseline.main(trainDir, testDir, outputDir_perspective)
# Convert baseline in perspective space into BEV space
# If your algorithm provides results in perspective space,
# you need to run this script before submission!
inputFiles = os.path.join(outputDir_perspective, '*.png')
transform2BEV.main(inputFiles, testData_pathToCalib, outputDir_bev)
# now zip the contents in the directory 'outputDir_bev' and upload
# the zip file to the KITTI server