def runMotionCudaBeliefPropRefineFromInputFloResults(inFloFile):
# retrieve the 'refining parameters' from the input flo file...
refiningParams = retrieveParamsRefineResults.retParamsToRefineResults(
inFloFile)
# set up the environment variables in order to run CUDA belief propagation
setupCudaBeliefProp.initToRunCudaBeliefProp()
# generate the input parameters to run CUDA belief propagation
inParamCudaBeliefProp = inputParamsMultImages.InputParamsMultImages()
# adjust the input parameters based on the 'flo' input...
inParamCudaBeliefProp.adjustParticParams(
refiningParams[
retrieveParamsRefineResultsConsts.START_MOVE_INC_X_PARAM_KEY],
refiningParams[
retrieveParamsRefineResultsConsts.START_MOVE_INC_Y_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MIN_X_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MAX_X_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MIN_Y_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MAX_Y_MOVE_PARAM_KEY])
# generate the header file for the current set of parameters defined in runMotionBeliefPropConsts.py
genHeaderFile.genCurrHeaderFile()
# clean and make cuda belief propagation
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(inParamCudaBeliefProp)
def runMotionCudaBeliefProp():
# set up the environment variables in order to run CUDA belief propagation
setupCudaBeliefProp.initToRunCudaBeliefProp()
# generate the input parameters to run CUDA belief propagation
inParamCudaBeliefProp = inputParamsRetrieveDataFromFloFiles.InputParamsRetrieveDataFromFloFiles(
)
# clean and make cuda belief propagation
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(inParamCudaBeliefProp)
def runMotionCudaBeliefProp():
# set up the environment variables in order to run CUDA belief propagation
setupCudaBeliefProp.initToRunCudaBeliefProp()
# generate the input parameters to run CUDA belief propagation
inParamCudaBeliefProp = inputParams.InputParams()
# generate the header file for the current set of parameters defined in runMotionBeliefPropConsts.py
genHeaderFile.genCurrHeaderFile()
# clean and make cuda belief propagation
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(inParamCudaBeliefProp)
def runMotionBeliefPropTakePrevMotionAndNoExpMotionResultIntoAccount():
# set up the environment variables in order to run CUDA belief propagation
setupCudaBeliefProp.initToRunCudaBeliefProp()
# retrieve the 'refining parameters' from the input flo file...
refiningParams = retrieveParamsRefineResults.retParamsToRefineResults(
runMotionBeliefPropGivenExpMotionInputs.FILE_PATH_EXPECTED_MOTION)
# generate the input parameters to run CUDA belief propagation
inParamCudaBeliefProp = inputParamsGivenExpMotion.InputParamsGivenExpMotion(
)
# adjust the input parameters based on the 'flo' input...
inParamCudaBeliefProp.adjustParticParams(
refiningParams[
retrieveParamsRefineResultsConsts.START_MOVE_INC_X_PARAM_KEY],
refiningParams[
retrieveParamsRefineResultsConsts.START_MOVE_INC_Y_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MIN_X_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MAX_X_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MIN_Y_MOVE_PARAM_KEY],
refiningParams[retrieveParamsRefineResultsConsts.MAX_Y_MOVE_PARAM_KEY])
# adjust the output 'movement' image
inParamCudaBeliefProp.adjustOutputMovementImage(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
FILE_PATH_OUTPUT_IMAGE_NO_ACCOUNT_EXP_MOTION)
# adjust the input parameter to save the flo motion...
inParamCudaBeliefProp.adjustOutputMotionFloFile(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
PATH_FLO_FILE_EXP_MOTION_NOT_USED)
# adjust the parameter to not take expected motion into account...
inParamCudaBeliefProp.adjustTakeExpMotionWeight(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
WEIGHT_EXP_MOTION_WHEN_NOT_USED)
# adjust the smoothing sigma
inParamCudaBeliefProp.adjustSmoothingSigmaInputImages(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
SMOOTHING_SIGMA_WHEN_EXP_MOTION_NOT_USED)
# generate the header file for the current set of parameters defined in runMotionBeliefPropConsts.py
genHeaderFile.genCurrHeaderFile()
# clean and make cuda belief propagation
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(inParamCudaBeliefProp)
# retrieve the motion data of the 'rough results'
motionDataRoughResults = motionData.MotionData()
motionDataRoughResults.readMotionFromFloFile(
runMotionBeliefPropGivenExpMotionInputs.FILE_PATH_EXPECTED_MOTION)
# retrieve the motion data of the results that don't use the expected motion
motionDontUseExpMotion = motionData.MotionData()
motionDontUseExpMotion.readMotionFromFloFile(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
PATH_FLO_FILE_EXP_MOTION_NOT_USED)
# merge the two results
motionDataRoughResults.mergeMotionData(motionDontUseExpMotion)
# save the merged results
motionDataRoughResults.saveMotionToFloFile(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
PATH_FLO_FILE_MERGED_RESULT_ACCOUNT_BOTH_MOTIONS)
# adjust the parameter to use the merged results
inParamCudaBeliefProp.adjustInputFloFile(
runMotionBeliefPropRefineFromFloResultsAndUseNoExpMoveFloResultConsts.
PATH_FLO_FILE_MERGED_RESULT_ACCOUNT_BOTH_MOTIONS)
# adjust the output 'movement' image
inParamCudaBeliefProp.adjustOutputMovementImage(
runMotionBeliefPropGivenExpMotionInputs.
FILE_PATH_SAVE_RESULTING_MOTION_IMAGE)
# adjust the parameter to take expected motion into account...
inParamCudaBeliefProp.adjustTakeExpMotionWeight(
runMotionBeliefPropGivenExpMotionInputs.
EST_MOVEMENT_WEIGHT_BP_MOTION_TEST)
# adjust the parameter for the flo file of the output motion
inParamCudaBeliefProp.adjustOutputMotionFloFile(
runMotionBeliefPropGivenExpMotionInputs.
FILE_PATH_SAVED_MOVEMENT_DATA_FLO_FORMAT)
# adjust the smoothing sigma
inParamCudaBeliefProp.adjustSmoothingSigmaInputImages(
runMotionBeliefPropGivenExpMotionInputs.SMOOTHING_SIGMA_BP_MOTION_TEST)
# now run the data using the merged results as the input 'flo' file...
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(inParamCudaBeliefProp)
def runMotionBpMultImagesAdjInputs():
# initialize a dictionary for all the results
allResultsDict = {}
# need a loop for each 'different' input
# make the 'data cost' adjustable
for currDataCost in runMotionBeliefPropMultImagesAdjInputsInVals.LIST_DATA_COST_CAPS:
# make the 'data weight' adjustable
for currDataWeight in runMotionBeliefPropMultImagesAdjInputsInVals.LIST_DATA_WEIGHTS:
# make the 'smoothness cost' adjustable
for currSmoothnessCost in runMotionBeliefPropMultImagesAdjInputsInVals.LIST_SMOOTHNESS_COST_CAPS:
# make the 'estimated movement weight' adjustable
for currEstMoveWeight in runMotionBeliefPropMultImagesAdjInputsInVals.LIST_EST_MOVE_WEIGHTS:
# make the 'estimated movement cost' adjustable
for currEstMoveCost in runMotionBeliefPropMultImagesAdjInputsInVals.LIST_EST_MOVE_COST_CAPS:
# initialize the dictionary with the current set of results
dictResultsSet = {
runMotionBeliefPropMultImagesAdjInputsConsts.DATA_COST_CAP_NAME_CONST:
currDataCost,
runMotionBeliefPropMultImagesAdjInputsConsts.DATA_WEIGHT_NAME_CONST:
currDataWeight,
runMotionBeliefPropMultImagesAdjInputsConsts.SMOOTHNESS_COST_CAP_NAME_CONST:
currSmoothnessCost,
runMotionBeliefPropMultImagesAdjInputsConsts.EST_MOVEMENT_WEIGHT_NAME_CONST:
currEstMoveWeight,
runMotionBeliefPropMultImagesAdjInputsConsts.EST_MOVEMENT_COST_CAP_NAME_CONST:
currEstMoveCost
}
# set up the environment variables in order to run CUDA belief propagation
setupCudaBeliefProp.initToRunCudaBeliefProp()
# generate the input parameters to run CUDA belief propagation
inParamCudaBeliefProp = inputParamsMultImages.InputParamsMultImages(
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_INPUT_IMAGE_FILE_BASE,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_START_IMAGE_NUM,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_END_IMAGE_NUM,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_END_EXTENSION,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_SAVE_RESULTING_MOTION_IMAGE,
runMotionBeliefPropMultImagesAdjInputsInVals.
WIDTH_INPUT_IMAGE_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
HEIGHT_INPUT_IMAGE_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
NUM_BELIEF_PROP_LEVELS_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
NUM_BELIEF_PROP_ITERS_PER_LEVEL_BP_MOTION_TEST,
currDataCost, currSmoothnessCost, currDataWeight,
runMotionBeliefPropMultImagesAdjInputsInVals.
CURRENT_MOVE_INCREMENT_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
SAMPLING_LEVEL_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
X_MOVE_MIN_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
X_MOVE_MAX_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
Y_MOVE_MIN_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
Y_MOVE_MAX_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
RANGE_DISPLAY_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
GROUND_TRUTH_MOVEMENT_FLO_FORMAT,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_PATH_SAVED_MOVEMENT_DATA_FLO_FORMAT,
runMotionBeliefPropMultImagesAdjInputsInVals.
PROP_CHANGE_MOVE_NEXT_LEVEL_BP_MOTION_TEST,
runMotionBeliefPropMultImagesAdjInputsInVals.
SMOOTHING_SIGMA_BP_MOTION_TEST, currEstMoveCost,
currEstMoveWeight)
# generate the header file for the current set of parameters defined in runMotionBeliefPropConsts.py
genHeaderFile.genCurrHeaderFile()
# clean and make cuda belief propagation
cleanAndMakeRunBeliefPropMotion.cleanMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
cleanAndMakeRunBeliefPropMotion.makeMotionBeliefProp(
runMotionBeliefPropConsts.DIR_MAKEFILE)
# run cuda belief propagation
exeBeliefPropMotion.runBeliefPropMotion(
inParamCudaBeliefProp,
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_SAVE_OUT_MOTION)
# extract the results as a dictionary
resultsDict = extractResultAsDict.retResultingDict(
runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_SAVE_OUT_MOTION)
# add the 'extracted results'
dictResultsSet.update(resultsDict)
print allResultsDict
# go through the set of results and add to the overall results...
for dictKey, dictVal in dictResultsSet.iteritems():
if (dictKey in allResultsDict.keys()):
allResultsDict[dictKey].append(dictVal)
else:
allResultsDict[dictKey] = [dictVal]
# delete the file with the saved info
os.remove(runMotionBeliefPropMultImagesAdjInputsInVals.
FILE_SAVE_OUT_MOTION)
print allResultsDict
# print the output dictionary
print allResultsDict
# write the results to a csv file...
writeOutputDictToCsv.writeOutputResultsCsvFile(
allResultsDict,
runMotionBeliefPropMultImagesAdjInputsInVals.FILE_OUT_MOTION_INFO)