parser.add_argument("mode", help="Trains or tests the CNN", nargs='+', choices=["train", "test", "slice", "identify"]) args = parser.parse_args() print("--------------------------") print("| ** Config ** ") print("| Validation ratio: {}".format(validationRatio)) print("| Test ratio: {}".format(testRatio)) print("| Slices per genre: {}".format(filesPerGenre)) print("| Slice size: {}".format(sliceSize)) print("--------------------------") if "slice" in args.mode: createSlicesFromAudio(trainPath) sys.exit() #List genres genres = os.listdir(trainPath + slicesPath) genres = [ filename for filename in genres if os.path.isdir(trainPath + slicesPath + filename) ] nbClasses = len(genres) #Create model model = createModel(nbClasses, sliceSize) if "train" in args.mode:
parser.add_argument("mode", help="Trains or tests the CNN", nargs='+', choices=["train", "test", "slice", "predict"]) args = parser.parse_args() print("--------------------------") print("| ** Config ** ") print("| Validation ratio: {}".format(validationRatio)) print("| Test ratio: {}".format(testRatio)) print("| Slices per genre: {}".format(filesPerGenre)) print("| Slice size: {}".format(sliceSize)) print("--------------------------") if "slice" in args.mode: createSlicesFromAudio() sys.exit() #List genres genres = os.listdir(slicesPath) genres = [ filename for filename in genres if os.path.isdir(slicesPath + filename) ] nbClasses = len(genres) #Create model model = createModel(nbClasses, sliceSize) if "train" in args.mode: #Create or load new dataset
import argparse parser = argparse.ArgumentParser() parser.add_argument("mode", help="Trains or tests the CNN", nargs='+', choices=["train","test","slice"]) args = parser.parse_args() print("--------------------------") print("| ** Config ** ") print("| Validation ratio: {}".format(validationRatio)) print("| Test ratio: {}".format(testRatio)) print("| Slices per genre: {}".format(filesPerGenre)) print("| Slice size: {}".format(sliceSize)) print("--------------------------") if "slice" in args.mode: createSlicesFromAudio() sys.exit() #List genres genres = os.listdir(slicesPath) genres = [filename for filename in genres if os.path.isdir(slicesPath+filename)] nbClasses = len(genres) #Create model model = createModel(nbClasses, sliceSize) if "train" in args.mode: #Create or load new dataset train_X, train_y, validation_X, validation_y = getDataset(filesPerGenre, genres, sliceSize, validationRatio, testRatio, mode="train")