gptsite

Runtime error

App Files Files Community

gptsite / gradio /processing_utils.py

microhan

update module gradio

d4576ce about 1 year ago

raw history blame contribute delete

No virus

28.9 kB

	from __future__ import annotations

	import base64
	import hashlib
	import json
	import mimetypes
	import os
	import secrets
	import shutil
	import subprocess
	import tempfile
	import urllib.request
	import warnings
	from io import BytesIO
	from pathlib import Path
	from typing import Dict, Set, Tuple

	import aiofiles
	import numpy as np
	import requests
	from fastapi import UploadFile
	from ffmpy import FFmpeg, FFprobe, FFRuntimeError
	from PIL import Image, ImageOps, PngImagePlugin

	from gradio import utils

	with warnings.catch_warnings():
	warnings.simplefilter("ignore") # Ignore pydub warning if ffmpeg is not installed
	from pydub import AudioSegment


	#########################
	# GENERAL
	#########################


	def to_binary(x: str \| Dict) -> bytes:
	"""Converts a base64 string or dictionary to a binary string that can be sent in a POST."""
	if isinstance(x, dict):
	if x.get("data"):
	base64str = x["data"]
	else:
	base64str = encode_url_or_file_to_base64(x["name"])
	else:
	base64str = x
	return base64.b64decode(base64str.split(",")[1])


	#########################
	# IMAGE PRE-PROCESSING
	#########################


	def decode_base64_to_image(encoding: str) -> Image.Image:
	content = encoding.split(";")[1]
	image_encoded = content.split(",")[1]
	img = Image.open(BytesIO(base64.b64decode(image_encoded)))
	exif = img.getexif()
	# 274 is the code for image rotation and 1 means "correct orientation"
	if exif.get(274, 1) != 1 and hasattr(ImageOps, "exif_transpose"):
	img = ImageOps.exif_transpose(img)
	return img


	def encode_url_or_file_to_base64(path: str \| Path):
	path = str(path)
	if utils.validate_url(path):
	return encode_url_to_base64(path)
	else:
	return encode_file_to_base64(path)


	def get_mimetype(filename: str) -> str \| None:
	mimetype = mimetypes.guess_type(filename)[0]
	if mimetype is not None:
	mimetype = mimetype.replace("x-wav", "wav").replace("x-flac", "flac")
	return mimetype


	def get_extension(encoding: str) -> str \| None:
	encoding = encoding.replace("audio/wav", "audio/x-wav")
	type = mimetypes.guess_type(encoding)[0]
	if type == "audio/flac": # flac is not supported by mimetypes
	return "flac"
	elif type is None:
	return None
	extension = mimetypes.guess_extension(type)
	if extension is not None and extension.startswith("."):
	extension = extension[1:]
	return extension


	def encode_file_to_base64(f):
	with open(f, "rb") as file:
	encoded_string = base64.b64encode(file.read())
	base64_str = str(encoded_string, "utf-8")
	mimetype = get_mimetype(f)
	return (
	"data:"
	+ (mimetype if mimetype is not None else "")
	+ ";base64,"
	+ base64_str
	)


	def encode_url_to_base64(url):
	encoded_string = base64.b64encode(requests.get(url).content)
	base64_str = str(encoded_string, "utf-8")
	mimetype = get_mimetype(url)
	return (
	"data:" + (mimetype if mimetype is not None else "") + ";base64," + base64_str
	)


	def encode_plot_to_base64(plt):
	with BytesIO() as output_bytes:
	plt.savefig(output_bytes, format="png")
	bytes_data = output_bytes.getvalue()
	base64_str = str(base64.b64encode(bytes_data), "utf-8")
	return "data:image/png;base64," + base64_str


	def save_array_to_file(image_array, dir=None):
	pil_image = Image.fromarray(_convert(image_array, np.uint8, force_copy=False))
	file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir)
	pil_image.save(file_obj)
	return file_obj


	def get_pil_metadata(pil_image):
	# Copy any text-only metadata
	metadata = PngImagePlugin.PngInfo()
	for key, value in pil_image.info.items():
	if isinstance(key, str) and isinstance(value, str):
	metadata.add_text(key, value)

	return metadata


	def save_pil_to_file(pil_image, dir=None):
	file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir)
	pil_image.save(file_obj, pnginfo=get_pil_metadata(pil_image))
	return file_obj


	def encode_pil_to_base64(pil_image):
	with BytesIO() as output_bytes:
	pil_image.save(output_bytes, "PNG", pnginfo=get_pil_metadata(pil_image))
	bytes_data = output_bytes.getvalue()
	base64_str = str(base64.b64encode(bytes_data), "utf-8")
	return "data:image/png;base64," + base64_str


	def encode_array_to_base64(image_array):
	with BytesIO() as output_bytes:
	pil_image = Image.fromarray(_convert(image_array, np.uint8, force_copy=False))
	pil_image.save(output_bytes, "PNG")
	bytes_data = output_bytes.getvalue()
	base64_str = str(base64.b64encode(bytes_data), "utf-8")
	return "data:image/png;base64," + base64_str


	def resize_and_crop(img, size, crop_type="center"):
	"""
	Resize and crop an image to fit the specified size.
	args:
	size: `(width, height)` tuple. Pass `None` for either width or height
	to only crop and resize the other.
	crop_type: can be 'top', 'middle' or 'bottom', depending on this
	value, the image will cropped getting the 'top/left', 'middle' or
	'bottom/right' of the image to fit the size.
	raises:
	ValueError: if an invalid `crop_type` is provided.
	"""
	if crop_type == "top":
	center = (0, 0)
	elif crop_type == "center":
	center = (0.5, 0.5)
	else:
	raise ValueError

	resize = list(size)
	if size[0] is None:
	resize[0] = img.size[0]
	if size[1] is None:
	resize[1] = img.size[1]
	return ImageOps.fit(img, resize, centering=center) # type: ignore


	##################
	# Audio
	##################


	def audio_from_file(filename, crop_min=0, crop_max=100):
	try:
	audio = AudioSegment.from_file(filename)
	except FileNotFoundError as e:
	isfile = Path(filename).is_file()
	msg = (
	f"Cannot load audio from file: `{'ffprobe' if isfile else filename}` not found."
	+ " Please install `ffmpeg` in your system to use non-WAV audio file formats"
	" and make sure `ffprobe` is in your PATH."
	if isfile
	else ""
	)
	raise RuntimeError(msg) from e
	if crop_min != 0 or crop_max != 100:
	audio_start = len(audio) * crop_min / 100
	audio_end = len(audio) * crop_max / 100
	audio = audio[audio_start:audio_end]
	data = np.array(audio.get_array_of_samples())
	if audio.channels > 1:
	data = data.reshape(-1, audio.channels)
	return audio.frame_rate, data


	def audio_to_file(sample_rate, data, filename):
	data = convert_to_16_bit_wav(data)
	audio = AudioSegment(
	data.tobytes(),
	frame_rate=sample_rate,
	sample_width=data.dtype.itemsize,
	channels=(1 if len(data.shape) == 1 else data.shape[1]),
	)
	file = audio.export(filename, format="wav")
	file.close() # type: ignore


	def convert_to_16_bit_wav(data):
	# Based on: https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.wavfile.write.html
	warning = "Trying to convert audio automatically from {} to 16-bit int format."
	if data.dtype in [np.float64, np.float32, np.float16]:
	warnings.warn(warning.format(data.dtype))
	data = data / np.abs(data).max()
	data = data * 32767
	data = data.astype(np.int16)
	elif data.dtype == np.int32:
	warnings.warn(warning.format(data.dtype))
	data = data / 65538
	data = data.astype(np.int16)
	elif data.dtype == np.int16:
	pass
	elif data.dtype == np.uint16:
	warnings.warn(warning.format(data.dtype))
	data = data - 32768
	data = data.astype(np.int16)
	elif data.dtype == np.uint8:
	warnings.warn(warning.format(data.dtype))
	data = data * 257 - 32768
	data = data.astype(np.int16)
	else:
	raise ValueError(
	"Audio data cannot be converted automatically from "
	f"{data.dtype} to 16-bit int format."
	)
	return data


	##################
	# OUTPUT
	##################


	def decode_base64_to_binary(encoding) -> Tuple[bytes, str \| None]:
	extension = get_extension(encoding)
	try:
	data = encoding.split(",")[1]
	except IndexError:
	data = ""
	return base64.b64decode(data), extension


	def decode_base64_to_file(encoding, file_path=None, dir=None, prefix=None):
	if dir is not None:
	os.makedirs(dir, exist_ok=True)
	data, extension = decode_base64_to_binary(encoding)
	if file_path is not None and prefix is None:
	filename = Path(file_path).name
	prefix = filename
	if "." in filename:
	prefix = filename[0 : filename.index(".")]
	extension = filename[filename.index(".") + 1 :]

	if prefix is not None:
	prefix = utils.strip_invalid_filename_characters(prefix)

	if extension is None:
	file_obj = tempfile.NamedTemporaryFile(delete=False, prefix=prefix, dir=dir)
	else:
	file_obj = tempfile.NamedTemporaryFile(
	delete=False,
	prefix=prefix,
	suffix="." + extension,
	dir=dir,
	)
	file_obj.write(data)
	file_obj.flush()
	return file_obj


	def dict_or_str_to_json_file(jsn, dir=None):
	if dir is not None:
	os.makedirs(dir, exist_ok=True)

	file_obj = tempfile.NamedTemporaryFile(
	delete=False, suffix=".json", dir=dir, mode="w+"
	)
	if isinstance(jsn, str):
	jsn = json.loads(jsn)
	json.dump(jsn, file_obj)
	file_obj.flush()
	return file_obj


	def file_to_json(file_path: str \| Path) -> Dict:
	with open(file_path) as f:
	return json.load(f)


	class TempFileManager:
	"""
	A class that should be inherited by any Component that needs to manage temporary files.
	It should be instantiated in the __init__ method of the component.
	"""

	def __init__(self) -> None:
	# Set stores all the temporary files created by this component.
	self.temp_files: Set[str] = set()
	self.DEFAULT_TEMP_DIR = tempfile.gettempdir()

	def hash_file(self, file_path: str, chunk_num_blocks: int = 128) -> str:
	sha1 = hashlib.sha1()
	with open(file_path, "rb") as f:
	for chunk in iter(lambda: f.read(chunk_num_blocks * sha1.block_size), b""):
	sha1.update(chunk)
	return sha1.hexdigest()

	def hash_url(self, url: str, chunk_num_blocks: int = 128) -> str:
	sha1 = hashlib.sha1()
	remote = urllib.request.urlopen(url)
	max_file_size = 100 * 1024 * 1024 # 100MB
	total_read = 0
	while True:
	data = remote.read(chunk_num_blocks * sha1.block_size)
	total_read += chunk_num_blocks * sha1.block_size
	if not data or total_read > max_file_size:
	break
	sha1.update(data)
	return sha1.hexdigest()

	def hash_base64(self, base64_encoding: str, chunk_num_blocks: int = 128) -> str:
	sha1 = hashlib.sha1()
	for i in range(0, len(base64_encoding), chunk_num_blocks * sha1.block_size):
	data = base64_encoding[i : i + chunk_num_blocks * sha1.block_size]
	sha1.update(data.encode("utf-8"))
	return sha1.hexdigest()

	def make_temp_copy_if_needed(self, file_path: str) -> str:
	"""Returns a temporary file path for a copy of the given file path if it does
	not already exist. Otherwise returns the path to the existing temp file."""
	temp_dir = self.hash_file(file_path)
	temp_dir = Path(self.DEFAULT_TEMP_DIR) / temp_dir
	temp_dir.mkdir(exist_ok=True, parents=True)

	f = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir)
	f.name = utils.strip_invalid_filename_characters(Path(file_path).name)
	full_temp_file_path = str(utils.abspath(temp_dir / f.name))

	if not Path(full_temp_file_path).exists():
	shutil.copy2(file_path, full_temp_file_path)

	self.temp_files.add(full_temp_file_path)
	return full_temp_file_path

	async def save_uploaded_file(self, file: UploadFile, upload_dir: str) -> str:
	temp_dir = secrets.token_hex(
	20
	) # Since the full file is being uploaded anyways, there is no benefit to hashing the file.
	temp_dir = Path(upload_dir) / temp_dir
	temp_dir.mkdir(exist_ok=True, parents=True)
	output_file_obj = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir)

	if file.filename:
	file_name = Path(file.filename).name
	output_file_obj.name = utils.strip_invalid_filename_characters(file_name)

	full_temp_file_path = str(utils.abspath(temp_dir / output_file_obj.name))

	async with aiofiles.open(full_temp_file_path, "wb") as output_file:
	while True:
	content = await file.read(100 * 1024 * 1024)
	if not content:
	break
	await output_file.write(content)

	return full_temp_file_path

	def download_temp_copy_if_needed(self, url: str) -> str:
	"""Downloads a file and makes a temporary file path for a copy if does not already
	exist. Otherwise returns the path to the existing temp file."""
	temp_dir = self.hash_url(url)
	temp_dir = Path(self.DEFAULT_TEMP_DIR) / temp_dir
	temp_dir.mkdir(exist_ok=True, parents=True)
	f = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir)

	f.name = utils.strip_invalid_filename_characters(Path(url).name)
	full_temp_file_path = str(utils.abspath(temp_dir / f.name))

	if not Path(full_temp_file_path).exists():
	with requests.get(url, stream=True) as r:
	with open(full_temp_file_path, "wb") as f:
	shutil.copyfileobj(r.raw, f)

	self.temp_files.add(full_temp_file_path)
	return full_temp_file_path

	def base64_to_temp_file_if_needed(
	self, base64_encoding: str, file_name: str \| None = None
	) -> str:
	"""Converts a base64 encoding to a file and returns the path to the file if
	the file doesn't already exist. Otherwise returns the path to the existing file."""
	temp_dir = self.hash_base64(base64_encoding)
	temp_dir = Path(self.DEFAULT_TEMP_DIR) / temp_dir
	temp_dir.mkdir(exist_ok=True, parents=True)

	guess_extension = get_extension(base64_encoding)
	if file_name:
	file_name = utils.strip_invalid_filename_characters(file_name)
	elif guess_extension:
	file_name = "file." + guess_extension
	else:
	file_name = "file"
	f = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir)
	f.name = file_name
	full_temp_file_path = str(utils.abspath(temp_dir / f.name))

	if not Path(full_temp_file_path).exists():
	data, _ = decode_base64_to_binary(base64_encoding)
	with open(full_temp_file_path, "wb") as fb:
	fb.write(data)

	self.temp_files.add(full_temp_file_path)
	return full_temp_file_path


	def download_tmp_copy_of_file(
	url_path: str, access_token: str \| None = None, dir: str \| None = None
	) -> tempfile._TemporaryFileWrapper:
	if dir is not None:
	os.makedirs(dir, exist_ok=True)
	headers = {"Authorization": "Bearer " + access_token} if access_token else {}
	prefix = Path(url_path).stem
	suffix = Path(url_path).suffix
	file_obj = tempfile.NamedTemporaryFile(
	delete=False,
	prefix=prefix,
	suffix=suffix,
	dir=dir,
	)
	with requests.get(url_path, headers=headers, stream=True) as r:
	with open(file_obj.name, "wb") as f:
	shutil.copyfileobj(r.raw, f)
	return file_obj


	def create_tmp_copy_of_file(
	file_path: str, dir: str \| None = None
	) -> tempfile._TemporaryFileWrapper:
	if dir is not None:
	os.makedirs(dir, exist_ok=True)
	prefix = Path(file_path).stem
	suffix = Path(file_path).suffix
	file_obj = tempfile.NamedTemporaryFile(
	delete=False,
	prefix=prefix,
	suffix=suffix,
	dir=dir,
	)
	shutil.copy2(file_path, file_obj.name)
	return file_obj


	def _convert(image, dtype, force_copy=False, uniform=False):
	"""
	Adapted from: https://github.com/scikit-image/scikit-image/blob/main/skimage/util/dtype.py#L510-L531

	Convert an image to the requested data-type.
	Warnings are issued in case of precision loss, or when negative values
	are clipped during conversion to unsigned integer types (sign loss).
	Floating point values are expected to be normalized and will be clipped
	to the range [0.0, 1.0] or [-1.0, 1.0] when converting to unsigned or
	signed integers respectively.
	Numbers are not shifted to the negative side when converting from
	unsigned to signed integer types. Negative values will be clipped when
	converting to unsigned integers.
	Parameters
	----------
	image : ndarray
	Input image.
	dtype : dtype
	Target data-type.
	force_copy : bool, optional
	Force a copy of the data, irrespective of its current dtype.
	uniform : bool, optional
	Uniformly quantize the floating point range to the integer range.
	By default (uniform=False) floating point values are scaled and
	rounded to the nearest integers, which minimizes back and forth
	conversion errors.
	.. versionchanged :: 0.15
	``_convert`` no longer warns about possible precision or sign
	information loss. See discussions on these warnings at:
	https://github.com/scikit-image/scikit-image/issues/2602
	https://github.com/scikit-image/scikit-image/issues/543#issuecomment-208202228
	https://github.com/scikit-image/scikit-image/pull/3575
	References
	----------
	.. [1] DirectX data conversion rules.
	https://msdn.microsoft.com/en-us/library/windows/desktop/dd607323%28v=vs.85%29.aspx
	.. [2] Data Conversions. In "OpenGL ES 2.0 Specification v2.0.25",
	pp 7-8. Khronos Group, 2010.
	.. [3] Proper treatment of pixels as integers. A.W. Paeth.
	In "Graphics Gems I", pp 249-256. Morgan Kaufmann, 1990.
	.. [4] Dirty Pixels. J. Blinn. In "Jim Blinn's corner: Dirty Pixels",
	pp 47-57. Morgan Kaufmann, 1998.
	"""
	dtype_range = {
	bool: (False, True),
	np.bool_: (False, True),
	np.bool8: (False, True),
	float: (-1, 1),
	np.float_: (-1, 1),
	np.float16: (-1, 1),
	np.float32: (-1, 1),
	np.float64: (-1, 1),
	}

	def _dtype_itemsize(itemsize, *dtypes):
	"""Return first of `dtypes` with itemsize greater than `itemsize`
	Parameters
	----------
	itemsize: int
	The data type object element size.
	Other Parameters
	----------------
	*dtypes:
	Any Object accepted by `np.dtype` to be converted to a data
	type object
	Returns
	-------
	dtype: data type object
	First of `dtypes` with itemsize greater than `itemsize`.
	"""
	return next(dt for dt in dtypes if np.dtype(dt).itemsize >= itemsize)

	def _dtype_bits(kind, bits, itemsize=1):
	"""Return dtype of `kind` that can store a `bits` wide unsigned int
	Parameters:
	kind: str
	Data type kind.
	bits: int
	Desired number of bits.
	itemsize: int
	The data type object element size.
	Returns
	-------
	dtype: data type object
	Data type of `kind` that can store a `bits` wide unsigned int
	"""

	s = next(
	i
	for i in (itemsize,) + (2, 4, 8)
	if bits < (i * 8) or (bits == (i * 8) and kind == "u")
	)

	return np.dtype(kind + str(s))

	def _scale(a, n, m, copy=True):
	"""Scale an array of unsigned/positive integers from `n` to `m` bits.
	Numbers can be represented exactly only if `m` is a multiple of `n`.
	Parameters
	----------
	a : ndarray
	Input image array.
	n : int
	Number of bits currently used to encode the values in `a`.
	m : int
	Desired number of bits to encode the values in `out`.
	copy : bool, optional
	If True, allocates and returns new array. Otherwise, modifies
	`a` in place.
	Returns
	-------
	out : array
	Output image array. Has the same kind as `a`.
	"""
	kind = a.dtype.kind
	if n > m and a.max() < 2**m:
	return a.astype(_dtype_bits(kind, m))
	elif n == m:
	return a.copy() if copy else a
	elif n > m:
	# downscale with precision loss
	if copy:
	b = np.empty(a.shape, _dtype_bits(kind, m))
	np.floor_divide(a, 2 ** (n - m), out=b, dtype=a.dtype, casting="unsafe")
	return b
	else:
	a //= 2 ** (n - m)
	return a
	elif m % n == 0:
	# exact upscale to a multiple of `n` bits
	if copy:
	b = np.empty(a.shape, _dtype_bits(kind, m))
	np.multiply(a, (2m - 1) // (2n - 1), out=b, dtype=b.dtype)
	return b
	else:
	a = a.astype(_dtype_bits(kind, m, a.dtype.itemsize), copy=False)
	a = (2m - 1) // (2*n - 1)
	return a
	else:
	# upscale to a multiple of `n` bits,
	# then downscale with precision loss
	o = (m // n + 1) * n
	if copy:
	b = np.empty(a.shape, _dtype_bits(kind, o))
	np.multiply(a, (2o - 1) // (2n - 1), out=b, dtype=b.dtype)
	b //= 2 ** (o - m)
	return b
	else:
	a = a.astype(_dtype_bits(kind, o, a.dtype.itemsize), copy=False)
	a = (2o - 1) // (2*n - 1)
	a //= 2 ** (o - m)
	return a

	image = np.asarray(image)
	dtypeobj_in = image.dtype
	if dtype is np.floating:
	dtypeobj_out = np.dtype("float64")
	else:
	dtypeobj_out = np.dtype(dtype)
	dtype_in = dtypeobj_in.type
	dtype_out = dtypeobj_out.type
	kind_in = dtypeobj_in.kind
	kind_out = dtypeobj_out.kind
	itemsize_in = dtypeobj_in.itemsize
	itemsize_out = dtypeobj_out.itemsize

	# Below, we do an `issubdtype` check. Its purpose is to find out
	# whether we can get away without doing any image conversion. This happens
	# when:
	#
	# - the output and input dtypes are the same or
	# - when the output is specified as a type, and the input dtype
	# is a subclass of that type (e.g. `np.floating` will allow
	# `float32` and `float64` arrays through)

	if np.issubdtype(dtype_in, np.obj2sctype(dtype)):
	if force_copy:
	image = image.copy()
	return image

	if kind_in in "ui":
	imin_in = np.iinfo(dtype_in).min
	imax_in = np.iinfo(dtype_in).max
	if kind_out in "ui":
	imin_out = np.iinfo(dtype_out).min # type: ignore
	imax_out = np.iinfo(dtype_out).max # type: ignore

	# any -> binary
	if kind_out == "b":
	return image > dtype_in(dtype_range[dtype_in][1] / 2)

	# binary -> any
	if kind_in == "b":
	result = image.astype(dtype_out)
	if kind_out != "f":
	result *= dtype_out(dtype_range[dtype_out][1])
	return result

	# float -> any
	if kind_in == "f":
	if kind_out == "f":
	# float -> float
	return image.astype(dtype_out)

	if np.min(image) < -1.0 or np.max(image) > 1.0:
	raise ValueError("Images of type float must be between -1 and 1.")
	# floating point -> integer
	# use float type that can represent output integer type
	computation_type = _dtype_itemsize(
	itemsize_out, dtype_in, np.float32, np.float64
	)

	if not uniform:
	if kind_out == "u":
	image_out = np.multiply(image, imax_out, dtype=computation_type) # type: ignore
	else:
	image_out = np.multiply(
	image, (imax_out - imin_out) / 2, dtype=computation_type # type: ignore
	)
	image_out -= 1.0 / 2.0
	np.rint(image_out, out=image_out)
	np.clip(image_out, imin_out, imax_out, out=image_out) # type: ignore
	elif kind_out == "u":
	image_out = np.multiply(image, imax_out + 1, dtype=computation_type) # type: ignore
	np.clip(image_out, 0, imax_out, out=image_out) # type: ignore
	else:
	image_out = np.multiply(
	image, (imax_out - imin_out + 1.0) / 2.0, dtype=computation_type # type: ignore
	)
	np.floor(image_out, out=image_out)
	np.clip(image_out, imin_out, imax_out, out=image_out) # type: ignore
	return image_out.astype(dtype_out)

	# signed/unsigned int -> float
	if kind_out == "f":
	# use float type that can exactly represent input integers
	computation_type = _dtype_itemsize(
	itemsize_in, dtype_out, np.float32, np.float64
	)

	if kind_in == "u":
	# using np.divide or np.multiply doesn't copy the data
	# until the computation time
	image = np.multiply(image, 1.0 / imax_in, dtype=computation_type) # type: ignore
	# DirectX uses this conversion also for signed ints
	# if imin_in:
	# np.maximum(image, -1.0, out=image)
	else:
	image = np.add(image, 0.5, dtype=computation_type)
	image *= 2 / (imax_in - imin_in) # type: ignore

	return np.asarray(image, dtype_out)

	# unsigned int -> signed/unsigned int
	if kind_in == "u":
	if kind_out == "i":
	# unsigned int -> signed int
	image = _scale(image, 8 * itemsize_in, 8 * itemsize_out - 1)
	return image.view(dtype_out)
	else:
	# unsigned int -> unsigned int
	return _scale(image, 8 * itemsize_in, 8 * itemsize_out)

	# signed int -> unsigned int
	if kind_out == "u":
	image = _scale(image, 8 * itemsize_in - 1, 8 * itemsize_out)
	result = np.empty(image.shape, dtype_out)
	np.maximum(image, 0, out=result, dtype=image.dtype, casting="unsafe")
	return result

	# signed int -> signed int
	if itemsize_in > itemsize_out:
	return _scale(image, 8 * itemsize_in - 1, 8 * itemsize_out - 1)

	image = image.astype(_dtype_bits("i", itemsize_out * 8))
	image -= imin_in # type: ignore
	image = _scale(image, 8 * itemsize_in, 8 * itemsize_out, copy=False)
	image += imin_out # type: ignore
	return image.astype(dtype_out)


	def ffmpeg_installed() -> bool:
	return shutil.which("ffmpeg") is not None


	def video_is_playable(video_filepath: str) -> bool:
	"""Determines if a video is playable in the browser.

	A video is playable if it has a playable container and codec.
	.mp4 -> h264
	.webm -> vp9
	.ogg -> theora
	"""
	try:
	container = Path(video_filepath).suffix.lower()
	probe = FFprobe(
	global_options="-show_format -show_streams -select_streams v -print_format json",
	inputs={video_filepath: None},
	)
	output = probe.run(stderr=subprocess.PIPE, stdout=subprocess.PIPE)
	output = json.loads(output[0])
	video_codec = output["streams"][0]["codec_name"]
	return (container, video_codec) in [
	(".mp4", "h264"),
	(".ogg", "theora"),
	(".webm", "vp9"),
	]
	# If anything goes wrong, assume the video can be played to not convert downstream
	except (FFRuntimeError, IndexError, KeyError):
	return True


	def convert_video_to_playable_mp4(video_path: str) -> str:
	"""Convert the video to mp4. If something goes wrong return the original video."""
	try:
	output_path = Path(video_path).with_suffix(".mp4")
	with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
	shutil.copy2(video_path, tmp_file.name)
	# ffmpeg will automatically use h264 codec (playable in browser) when converting to mp4
	ff = FFmpeg(
	inputs={str(tmp_file.name): None},
	outputs={str(output_path): None},
	global_options="-y -loglevel quiet",
	)
	ff.run()
	except FFRuntimeError as e:
	print(f"Error converting video to browser-playable format {str(e)}")
	output_path = video_path
	return str(output_path)