def main(): experimentName = 'Blstm_rawJoint' mConfig = getConfig(experimentName, 'False') dataset = 'chalearn' #workingDir = '/wrk/hshi/DONOTREMOVE/git/FeatureLearningAndGestureRecognition/ExperimentArchive/New/20180418' experimentDir = os.path.join(workingDir, experimentName) if not os.path.exists(experimentDir): os.mkdir(experimentDir) mConfig.workingDir = experimentDir mConfig.baseLearningRate = 0.0002 mData = Ntu(mConfig.dataPath, mConfig) batchSource_train, batchSource_test, batchSource_valid, segLen_max, sampleDim, frameLabelList_train, frameLabelList_test, frameLabelList_valid = mData.getData(mConfig) mNet = Blstm_v1(sampleDim, segLen_max, mConfig) mNet.train(6000, mConfig.batchSize_train, batchSource_train, mConfig.batchSize_test, batchSource_test)
def main(): experimentName = 'MyVae_selfReconstruction_relativeJoint_zClassification' args = parseArgs() finetune = args.finetune mConfig = getConfig(experimentName, finetune) dataset = 'chalearn' experimentDir = os.path.join(workingDir, experimentName) if not os.path.exists(experimentDir): os.mkdir(experimentDir) mConfig.workingDir = experimentDir mConfig.relativeJointFeature = True mData = Ntu(mConfig.dataPath, mConfig) batchSource_train, batchSource_test, batchSource_valid, segLen_max, sampleDim, frameLabelList_train, frameLabelList_test, frameLabelList_valid = mData.getData( mConfig) mNet = VaeBlstm_v7(sampleDim, segLen_max, mConfig) mNet.train(6000, mConfig.batchSize_train, batchSource_train, mConfig.batchSize_test, batchSource_test)
def main(): experimentName = 'StandardVae_selfReconstruction_relativeJoint_reconstructionClassification' dataset = 'chalearn' #workingDir = '/wrk/hshi/DONOTREMOVE/git/FeatureLearningAndGestureRecognition/ExperimentArchive/New/20180418' experimentDir = os.path.join(workingDir, experimentName) args = parseArgs() finetune = args.finetune mConfig = getConfig(experimentName, finetune) if not os.path.exists(experimentDir): os.mkdir(experimentDir) mConfig.workingDir = experimentDir mConfig.relativeJointFeature = True mData = Ntu(mConfig.dataPath, mConfig) batchSource_train, batchSource_test, batchSource_valid, segLen_max, sampleDim, frameLabelList_train, frameLabelList_test, frameLabelList_valid = mData.getData( mConfig) mNet = VaeBlstm_v12(sampleDim, segLen_max, mConfig) mNet.train(6000, mConfig.batchSize_train, batchSource_train, mConfig.batchSize_test, batchSource_test)