def main():
if len(sys.argv) < 2:
sys.exit("no file passed")
imgpath = sys.argv[1]
image = images.get_grayscale_picture(imgpath)
if image == None:
sys.exit("could not read image")
resized = images.resize_with_padding(image, 30, 50)
flattened = numpy.ravel(resized)
symbol = classify(flattened, "symbol")
if symbol == "note":
note_duration = classify(flattened, "note_duration")
pitch = classify(flattened, "pitch")
print(symbol, note_duration, pitch)
xmlpath = "demo/" + os.path.splitext(
os.path.basename(imgpath))[0] + ".xml"
musicxml.create_xml_for_note(pitch, note_duration, xmlpath)
elif symbol == "rest":
rest_duration = classify(flattened, "rest_duration")
print(symbol, rest_duration)
def get_data(dirname, files, classifier_func, m=PIXELS):
n = len(files)
X = np.zeros(shape=(n, m))
y = np.zeros(shape=(n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(dirname + filename)
klass = classifier_func(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def get_data(dirname, files, classifier_func, m = PIXELS):
n = len(files)
X = np.zeros(shape = (n, m))
y = np.zeros(shape = (n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(dirname + filename)
klass = classifier_func(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def get_notes(inputdir, m=PIXELS):
files = [f for f in os.listdir(inputdir) if f.startswith("note")]
n = len(files)
X = np.zeros(shape=(n, m))
y = np.zeros(shape=(n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = classes.get_pitch_class(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def old_get_data(inputdir, m=PIXELS):
files = [f for f in os.listdir(inputdir) if f.endswith(".png")]
n = len(files)
X = np.zeros(shape=(n, m))
y = np.zeros(shape=(n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = get_symbol_class(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def get_quarters_and_eights(inputdir, m = PIXELS):
files = [f for f in os.listdir(inputdir) if (f.startswith("note") and ("quarter" in f or "eighth" in f))]
n = len(files)
X = np.zeros(shape = (n, m))
y = np.zeros(shape = (n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = 0 if ("quarter" in filename) else 1
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def get_notes(inputdir, m = PIXELS):
files = [f for f in os.listdir(inputdir) if f.startswith("note")]
n = len(files)
X = np.zeros(shape = (n, m))
y = np.zeros(shape = (n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = classes.get_pitch_class(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def old_get_data(inputdir, m = PIXELS):
files = [f for f in os.listdir(inputdir) if f.endswith(".png")]
n = len(files)
X = np.zeros(shape = (n, m))
y = np.zeros(shape = (n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = get_symbol_class(filename)
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
def get_quarters_and_eights(inputdir, m=PIXELS):
files = [
f for f in os.listdir(inputdir)
if (f.startswith("note") and ("quarter" in f or "eighth" in f))
]
n = len(files)
X = np.zeros(shape=(n, m))
y = np.zeros(shape=(n, 1))
for (i, filename) in enumerate(files):
image = images.get_grayscale_picture(inputdir + filename)
klass = 0 if ("quarter" in filename) else 1
X[i] = np.ravel(image / 255)
y[i] = klass
return (X, y)
