def _open_gui(
stdscr,
filenames,
rows=1,
cols=1,
cmap=DEFAULTS["cmap"],
spec=True,
amp=True,
min_freq=var.DEFAULT_SPECTROGRAM_MIN_FREQ,
max_freq=var.DEFAULT_SPECTROGRAM_MAX_FREQ,
characters="quarter",
debug=False,
):
# files = gather_files(filenames, "wav", filter_with_readers=[AudioReader])
files = gather_files(filenames, "wav")
if not len(files):
click.echo("No files matching {} were found.".format(filenames))
return
transforms = []
if spec:
transform = DEFAULTS["audio"]["spec_transform"]
transform.min_freq = min_freq
transform.max_freq = max_freq
transforms.append(transform)
if amp:
transforms.append(DEFAULTS["audio"]["amp_transform"])
if not len(transforms):
click.echo("spec or amp (or both) must be selected")
return
charmap = get_char_map(characters)
app = InspecAudioApp(
rows,
cols,
files=files,
file_reader=AudioReader,
cmap=cmap,
view_class=AudioFileView,
transform=transforms,
map=charmap,
debug=debug
)
asyncio.run(app.main(stdscr))
def imshow(
filename,
height=None,
width=None,
cmap=None,
vertical=False,
characters="quarter",
thumbnail=False
):
cmap = load_cmap(cmap or var.DEFAULT_CMAP)
termsize = os.get_terminal_size()
if height and isinstance(height, float) and 0 < height <= 1:
height = int(np.round(termsize.lines * height))
elif height:
height = int(height)
if width and isinstance(width, float) and 0 < width <= 1:
width = int(np.round(termsize.columns * width))
elif width:
width = int(width)
charmap = get_char_map(characters)
height = height or termsize.lines
width = width or termsize.columns
if vertical:
height, width = width, height
desired_size = charmap.max_img_shape(height, width)
data, _ = PILImageReader.read_file(filename)
img, metadata = DEFAULTS["image"]["transform"].convert(
data,
output_size=desired_size,
size_multiple_of=charmap.patch_dimensions,
rotated=vertical,
)
if vertical:
img = img.T
char_array = charmap.to_char_array(img)
char_array = StdoutRenderer.apply_cmap_to_char_array(cmap, char_array)
StdoutRenderer.render(char_array)
def _listen(
stdscr,
device,
mode="amp",
chunk_size=1024,
step_chunks=2,
step_chars=None,
channels=1,
duration=2.0,
cmap=None,
min_freq=var.DEFAULT_SPECTROGRAM_MIN_FREQ,
max_freq=var.DEFAULT_SPECTROGRAM_MAX_FREQ,
characters="quarter",
debug=False,
):
if mode == "amp":
transform = AmplitudeEnvelopeTwoSidedTransform(ymax=500.0, gradient=(0.1, 1.0))
elif mode == "spec":
transform = DEFAULTS["audio"]["spec_transform"]
if min_freq is not None:
transform.min_freq = min_freq
if max_freq is not None:
transform.max_freq = max_freq
app = LiveAudioViewApp(
device=device,
mode=mode,
chunk_size=chunk_size,
step_chunks=step_chunks,
step_chars=step_chars,
channels=channels,
duration=duration,
transform=transform,
map=get_char_map(characters),
cmap=cmap,
debug=debug,
refresh_rate=30,
padx=2,
pady=2
)
asyncio.run(app.main(stdscr))
def _open_image_gui(
stdscr,
filenames,
rows=1,
cols=1,
cmap=DEFAULTS["cmap"],
characters="quarter",
debug=False,
):
# Need to be careful if validating a large number of files is too slow
files = gather_files(filenames, "*", filter_with_readers=[PILImageReader])
# files = gather_files(filenames, "*")
if not len(files):
click.echo("No files matching {} were found.".format(filenames))
return
transforms = [
PilImageGreyscaleTransform(thumbnail=False),
PilImageGreyscaleTransform(thumbnail=True),
]
charmap = get_char_map(characters)
app = InspecImageApp(
rows,
cols,
files=files,
file_reader=PILImageReader,
cmap=cmap,
view_class=ImageFileView,
transform=transforms,
map=charmap,
debug=debug
)
asyncio.run(app.main(stdscr))
def show(
filename,
height=None,
width=None,
duration=None,
time_=None,
channel=None,
cmap=None,
show_spec=True,
show_amp=False,
min_freq=var.DEFAULT_SPECTROGRAM_MIN_FREQ,
max_freq=var.DEFAULT_SPECTROGRAM_MAX_FREQ,
vertical=False,
characters="quarter",
):
cmap = load_cmap(cmap or var.DEFAULT_CMAP)
termsize = os.get_terminal_size()
if height and isinstance(height, float) and 0 < height <= 1:
height = int(np.round(termsize.lines * height))
elif height:
height = int(height)
if width and isinstance(width, float) and 0 < width <= 1:
width = int(np.round(termsize.columns * width))
elif width:
width = int(width)
is_audio = True
if is_audio:
charmap = get_char_map(characters)
height = height or termsize.lines
width = width or termsize.columns
if show_spec and show_amp:
height = height // 2
if vertical:
height, width = width, height
desired_size = charmap.max_img_shape(height, width)
if channel is None:
channel = 0
data, sampling_rate, _ = AudioReader.read_file_by_time(
filename,
duration=duration,
time_start=time_,
channel=channel
)
if show_spec:
transform = DEFAULTS["audio"]["spec_transform"]
transform.min_freq = min_freq
transform.max_freq = max_freq
img, metadata = DEFAULTS["audio"]["spec_transform"].convert(
data,
sampling_rate,
output_size=desired_size
)
if vertical:
img = img.T
char_array = charmap.to_char_array(img)
char_array = StdoutRenderer.apply_cmap_to_char_array(cmap, char_array)
StdoutRenderer.render(char_array)
if show_amp:
img, metadata = DEFAULTS["audio"]["amp_transform"].convert(
data,
sampling_rate,
output_size=desired_size
)
if vertical:
img = img.T
char_array = charmap.to_char_array(img)
char_array = StdoutRenderer.apply_cmap_to_char_array(cmap, char_array)
StdoutRenderer.render(char_array)