def main(argv):
seq = argv[0]
print seq
datasetDir = '/home/morris/var/media/Elements/var/data/KITTI/data_road/training/'
outputDir = '/home/morris/var/media/Elements/var/data/KITTI/data_road/LibLinear_Results/' + seq + '/grabcut_' + argv[1] + '_' + argv[2] + '_' + argv[3] + '/'
evaluateRoad.main(outputDir, datasetDir)
"Not deleting result files in the directory. Aborting now...")
sys.exit()
# Needs only to be called once, creates and stores ALL parameter files to paramDirName
# Can be commented out, if they already exist from an earlier run...
# cpf.createParameterFiles()
# Get a list with the names of all pngs used to detect lanes in
inputPngs = getPngs(inputDirName)
# Get a list with all parameter file names
paramFiles = getParameterFiles(paramDirName, 2520, 3479)
for pf in paramFiles:
print(
"#################### eval: current paramFile {} #######################"
.format(pf))
suffix = getSuffix(pf)
# Call for all images the binary for one specific parameter file
for png in inputPngs:
exitCode = callBinary(png, pf)
storeExitcodes(
exitCode,
os.path.abspath(os.path.join(resultsDirName, "exit" + suffix)))
# => output images of binary now exist in directory tmpDirName
# Call fct main() evaluateRoad.py on each of output images in tmpDirName
er.main(os.path.abspath(tmpDirName), os.path.abspath(imagesDirName),
os.path.abspath(os.path.join(resultsDirName, "data" + suffix)),
False)
# => one addtional measurement file "data123" in resultDirName
# Delete all images in tmpDirName
deleteImages(os.path.abspath(tmpDirName))
#datasetDir = '/hri/storage/user/rtds/KITTI_Road_Data'
#outputDir = '/hri/recordings/KITTI/road_dataset/'
# check for correct number of arguments.
if len(sys.argv)<2:
print("Usage: python simpleExample_evalTrainResults.py <datasetDir> <outputDir>")
print("<datasetDir> = base directory of the KITTI Road benchmark dataset (has to contain training and testing), e.g., /home/elvis/kitti_road/")
print("<outputDir> = Here the baseline results will be saved, e.g., /home/elvis/kitti_road/results/")
sys.exit(1)
# 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')
# Run computeBaseline script to generate example classification results on training set
trainDir = os.path.join(datasetDir, 'training')
outputDir_perspective = os.path.join(outputDir, 'baseline_perspective_train')
computeBaseline.main(trainDir, trainDir, outputDir_perspective)
# Toy example running evaluation on perspective train data
# Final evaluation on server is done in BEV space and uses a 'valid_map'
# indicating the BEV areas that are invalid
# (no correspondence in perspective space)
evaluateRoad.main(outputDir_perspective, trainDir)
# datasetDir = '/hri/storage/user/rtds/KITTI_Road_Data'
# outputDir = '/hri/recordings/KITTI/road_dataset/'
# check for correct number of arguments.
if len(sys.argv) < 2:
print "Usage: python simpleExample_evalTrainResults.py <datasetDir> <outputDir>"
print "<datasetDir> = base directory of the KITTI Road benchmark dataset (has to contain training and testing), e.g., /home/elvis/kitti_road/"
print "<outputDir> = Here the baseline results will be saved, e.g., /home/elvis/kitti_road/results/"
sys.exit(1)
# 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")
# Run computeBaseline script to generate example classification results on training set
trainDir = os.path.join(datasetDir, "training")
outputDir_perspective = os.path.join(outputDir, "baseline_perspective_train")
computeBaseline.main(trainDir, trainDir, outputDir_perspective)
# Toy example running evaluation on perspective train data
# Final evaluation on server is done in BEV space and uses a 'valid_map'
# indicating the BEV areas that are invalid
# (no correspondence in perspective space)
evaluateRoad.main(outputDir_perspective, trainDir)
import os, sys
import computeBaseline, evaluateRoad
if __name__ == "__main__":
assert len(sys.argv) == 3, "Usage : python myeval.py <result_dir> <data_road_dir>"
result_dir = sys.argv[1]
dataset_dir = sys.argv[2]
trainDir = os.path.join(dataset_dir, "training")
evaluateRoad.main(result_dir, trainDir)
