示例#1
0
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "inputList",  #nargs="1" , 
        help="Testing sample list.",
        #default=config.defaultGenScore
    )
    parser.add_argument(
        "modelFilename",  #nargs="1" , 
        help="Model filename",
        #default=config.defaultModelFilename
    )
    parser.add_argument("outputDir",
                        nargs="?",
                        help="Music output directory",
                        default=config.defaultOutputDir)
    args = parser.parse_args()

    genList = sampleLoader.parseFileList(args.inputList)
    for genFilename in genList:
        cmd = ["./musicPupilGen.py"]
        cmd.append(genFilename)
        cmd.append(args.modelFilename)
        cmd.append(args.outputDir)

        #logging.printDebug(" ".join(cmd))
        subprocess.call(" ".join(cmd), shell=True)
示例#2
0
def main():
   parser = argparse.ArgumentParser()
   parser.add_argument("inputList", #nargs="?" , 
                       help=("Training sample list."),
                       #default=config.defaultTrainSampleList
                      )
   parser.add_argument("outputDir", nargs="?" , 
                       help="Music output directory",
                       default = config.defaultOutputDir
                      )
   #parser.add_argument("modelName", nargs="?" , 
   #                    help="model filename",
   #                    default=config.defaultModelFilename
   #                    )
   args = parser.parse_args()


   trainSampList = sampleLoader.parseFileList(args.inputList)

   trainFeatsList = []
   for trainSampFilename in trainSampList:
      trainSamp = sampleLoader.loadTrainSample(trainSampFilename)
      trainFeat = featureManager.extractTrainFeat(trainSamp)
      trainFeatsList.append(trainFeat)

   trainFeatFilename = config.getTrainInFeatFilename(args)
   featureManager.saveJson(trainFeatsList, trainFeatFilename);

   m = model.getModelObj();
   #modelName = config.getModelFilename(args)
   m.train(args); #load features from config.getTrainInFeatFilename(args)
示例#3
0
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "inputList",  #nargs="?" , 
        help=("Training sample list."),
        #default=config.defaultTrainSampleList
    )
    parser.add_argument("outputDir",
                        nargs="?",
                        help="Music output directory",
                        default=config.defaultOutputDir)
    #parser.add_argument("modelName", nargs="?" ,
    #                    help="model filename",
    #                    default=config.defaultModelFilename
    #                    )
    args = parser.parse_args()

    trainSampList = sampleLoader.parseFileList(args.inputList)

    trainFeatsList = []
    for trainSampFilename in trainSampList:
        trainSamp = sampleLoader.loadTrainSample(trainSampFilename)
        trainFeat = featureManager.extractTrainFeat(trainSamp)
        trainFeatsList.append(trainFeat)

    trainFeatFilename = config.getTrainInFeatFilename(args)
    featureManager.saveJson(trainFeatsList, trainFeatFilename)

    m = model.getModelObj()
    #modelName = config.getModelFilename(args)
    m.train(args)
示例#4
0
def main():
   parser = argparse.ArgumentParser()
   parser.add_argument("inputList", #nargs="1" , 
                       help="Testing sample list.",
                       #default=config.defaultGenScore
                      )
   parser.add_argument("modelFilename", #nargs="1" , 
                       help="Model filename",
                       #default=config.defaultModelFilename
                      )
   parser.add_argument("outputDir", nargs="?" , 
                       help="Music output directory",
                       default = config.defaultOutputDir
                      )
   args = parser.parse_args()


   genList= sampleLoader.parseFileList(args.inputList)
   for genFilename in genList:
         cmd = ["./musicPupilGen.py"]
         cmd.append(genFilename)
         cmd.append(args.modelFilename)
         cmd.append(args.outputDir)

         #logging.printDebug(" ".join(cmd))
         subprocess.call(" ".join(cmd), shell=True)
import config
import sampleLoader
import featureManager
trainSampList = sampleLoader.parseFileList(config.unittestTrainSampleList)
for trainSampFilename in trainSampList:
    print("[INFO] Testing training sample: " + trainSampFilename)
    trainSamp = sampleLoader.loadTrainSample(trainSampFilename)

    print("[INFO] Extracting samples")
    trainFeat = featureManager.extractTrainFeat(trainSamp)
    #print(trainFeat)
    print(trainFeat['scoreFeats'])
    for key, feat in trainFeat['scoreFeats'].items():
        print(key)
        assert (
            len(feat) == 4
        ), 'the number of feature points doesn\'t match the test sample'
    for key, feat in trainFeat['perfFeats'].items():
        print(key)
        assert (
            len(feat) == 4
        ), 'the number of feature points doesn\'t match the test sample'

print('Tests passed')
import config
import sampleLoader
import featureManager 
trainSampList = sampleLoader.parseFileList(config.unittestTrainSampleList)
for trainSampFilename in trainSampList:
   print("[INFO] Testing training sample: " + trainSampFilename)
   trainSamp = sampleLoader.loadTrainSample(trainSampFilename)

   print("[INFO] Extracting samples")
   trainFeat = featureManager.extractTrainFeat(trainSamp)
   #print(trainFeat)
   print(trainFeat['scoreFeats'])
   for key,feat in trainFeat['scoreFeats'].items():
      print(key)
      assert(len(feat) == 4), 'the number of feature points doesn\'t match the test sample'
   for key, feat in trainFeat['perfFeats'].items():
      print(key)
      assert(len(feat) == 4), 'the number of feature points doesn\'t match the test sample'


print('Tests passed')