Files
2026-01-09 10:28:44 +11:00

1161 lines
41 KiB
Python

import sys
from enum import IntEnum
import cython
from cython.cimports.av.error import err_check
from cython.cimports.av.sidedata.sidedata import get_display_rotation
from cython.cimports.av.utils import check_ndarray
from cython.cimports.av.video.format import get_pix_fmt, get_video_format
from cython.cimports.av.video.plane import VideoPlane
from cython.cimports.libc.stdint import uint8_t
_cinit_bypass_sentinel = object()
# `pix_fmt`s supported by Frame.to_ndarray() and Frame.from_ndarray()
supported_np_pix_fmts = {
"abgr",
"argb",
"bayer_bggr16be",
"bayer_bggr16le",
"bayer_bggr8",
"bayer_gbrg16be",
"bayer_gbrg16le",
"bayer_gbrg8",
"bayer_grbg16be",
"bayer_grbg16le",
"bayer_grbg8",
"bayer_rggb16be",
"bayer_rggb16le",
"bayer_rggb8",
"bgr24",
"bgr48be",
"bgr48le",
"bgr8",
"bgra",
"bgra64be",
"bgra64le",
"gbrap",
"gbrap10be",
"gbrap10le",
"gbrap12be",
"gbrap12le",
"gbrap14be",
"gbrap14le",
"gbrap16be",
"gbrap16le",
"gbrapf32be",
"gbrapf32le",
"gbrp",
"gbrp10be",
"gbrp10le",
"gbrp12be",
"gbrp12le",
"gbrp14be",
"gbrp14le",
"gbrp16be",
"gbrp16le",
"gbrp9be",
"gbrp9le",
"gbrpf32be",
"gbrpf32le",
"gray",
"gray10be",
"gray10le",
"gray12be",
"gray12le",
"gray14be",
"gray14le",
"gray16be",
"gray16le",
"gray8",
"gray9be",
"gray9le",
"grayf32be",
"grayf32le",
"nv12",
"pal8",
"rgb24",
"rgb48be",
"rgb48le",
"rgb8",
"rgba",
"rgba64be",
"rgba64le",
"rgbaf16be",
"rgbaf16le",
"rgbaf32be",
"rgbaf32le",
"rgbf32be",
"rgbf32le",
"yuv420p",
"yuv422p10le",
"yuv444p",
"yuv444p16be",
"yuv444p16le",
"yuva444p16be",
"yuva444p16le",
"yuvj420p",
"yuvj444p",
"yuyv422",
}
@cython.cfunc
def alloc_video_frame() -> VideoFrame:
"""Get a mostly uninitialized VideoFrame.
You MUST call VideoFrame._init(...) or VideoFrame._init_user_attributes()
before exposing to the user.
"""
return VideoFrame(_cinit_bypass_sentinel)
class PictureType(IntEnum):
NONE = lib.AV_PICTURE_TYPE_NONE # Undefined
I = lib.AV_PICTURE_TYPE_I # Intra
P = lib.AV_PICTURE_TYPE_P # Predicted
B = lib.AV_PICTURE_TYPE_B # Bi-directional predicted
S = lib.AV_PICTURE_TYPE_S # S(GMC)-VOP MPEG-4
SI = lib.AV_PICTURE_TYPE_SI # Switching intra
SP = lib.AV_PICTURE_TYPE_SP # Switching predicted
BI = lib.AV_PICTURE_TYPE_BI # BI type
@cython.cfunc
def byteswap_array(array, big_endian: cython.bint):
if (sys.byteorder == "big") != big_endian:
return array.byteswap()
return array
@cython.cfunc
def copy_bytes_to_plane(
img_bytes,
plane: VideoPlane,
bytes_per_pixel: cython.uint,
flip_horizontal: cython.bint,
flip_vertical: cython.bint,
):
i_buf: cython.const[uint8_t][:] = img_bytes
i_pos: cython.size_t = 0
i_stride: cython.size_t = plane.width * bytes_per_pixel
o_buf: uint8_t[:] = plane
o_pos: cython.size_t = 0
o_stride: cython.size_t = abs(plane.line_size)
start_row, end_row, step = cython.declare(cython.int)
if flip_vertical:
start_row = plane.height - 1
end_row = -1
step = -1
else:
start_row = 0
end_row = plane.height
step = 1
for row in range(start_row, end_row, step):
i_pos = row * i_stride
if flip_horizontal:
for i in range(0, i_stride, bytes_per_pixel):
for j in range(bytes_per_pixel):
o_buf[o_pos + i + j] = i_buf[
i_pos + i_stride - i - bytes_per_pixel + j
]
else:
o_buf[o_pos : o_pos + i_stride] = i_buf[i_pos : i_pos + i_stride]
o_pos += o_stride
@cython.cfunc
def copy_array_to_plane(array, plane: VideoPlane, bytes_per_pixel: cython.uint):
imgbytes: bytes = array.tobytes()
copy_bytes_to_plane(imgbytes, plane, bytes_per_pixel, False, False)
@cython.cfunc
def useful_array(
plane: VideoPlane, bytes_per_pixel: cython.uint = 1, dtype: str = "uint8"
):
"""
Return the useful part of the VideoPlane as a single dimensional array.
We are simply discarding any padding which was added for alignment.
"""
import numpy as np
total_line_size: cython.size_t = abs(plane.line_size)
useful_line_size: cython.size_t = plane.width * bytes_per_pixel
arr = np.frombuffer(plane, np.uint8)
if total_line_size != useful_line_size:
arr = arr.reshape(-1, total_line_size)[:, 0:useful_line_size].reshape(-1)
return arr.view(np.dtype(dtype))
@cython.cfunc
def check_ndarray_shape(array: object, ok: cython.bint):
if not ok:
raise ValueError(f"Unexpected numpy array shape `{array.shape}`")
@cython.cclass
class VideoFrame(Frame):
def __cinit__(self, width=0, height=0, format="yuv420p"):
if width is _cinit_bypass_sentinel:
return
c_format: lib.AVPixelFormat = get_pix_fmt(format)
self._init(c_format, width, height)
@cython.cfunc
def _init(self, format: lib.AVPixelFormat, width: cython.uint, height: cython.uint):
res: cython.int = 0
with cython.nogil:
self.ptr.width = width
self.ptr.height = height
self.ptr.format = format
# We enforce aligned buffers, otherwise `sws_scale` can perform
# poorly or even cause out-of-bounds reads and writes.
if width and height:
res = lib.av_image_alloc(
self.ptr.data, self.ptr.linesize, width, height, format, 16
)
self._buffer = self.ptr.data[0]
if res:
err_check(res)
self._init_user_attributes()
@cython.cfunc
def _init_user_attributes(self):
self.format = get_video_format(
cython.cast(lib.AVPixelFormat, self.ptr.format),
self.ptr.width,
self.ptr.height,
)
def __dealloc__(self):
# The `self._buffer` member is only set if *we* allocated the buffer in `_init`,
# as opposed to a buffer allocated by a decoder.
lib.av_freep(cython.address(self._buffer))
# Let go of the reference from the numpy buffers if we made one
self._np_buffer = None
def __repr__(self):
return (
f"<av.{self.__class__.__name__}, pts={self.pts} {self.format.name} "
f"{self.width}x{self.height} at 0x{id(self):x}>"
)
@property
def planes(self):
"""
A tuple of :class:`.VideoPlane` objects.
"""
# We need to detect which planes actually exist, but also constrain ourselves to
# the maximum plane count (as determined only by VideoFrames so far), in case
# the library implementation does not set the last plane to NULL.
max_plane_count: cython.int = 0
for i in range(self.format.ptr.nb_components):
count = self.format.ptr.comp[i].plane + 1
if max_plane_count < count:
max_plane_count = count
if self.format.name == "pal8":
max_plane_count = 2
plane_count: cython.int = 0
while plane_count < max_plane_count and self.ptr.extended_data[plane_count]:
plane_count += 1
return tuple([VideoPlane(self, i) for i in range(plane_count)])
@property
def width(self):
"""Width of the image, in pixels."""
return self.ptr.width
@property
def height(self):
"""Height of the image, in pixels."""
return self.ptr.height
@property
def rotation(self):
"""The rotation component of the `DISPLAYMATRIX` transformation matrix.
Returns:
int: The angle (in degrees) by which the transformation rotates the frame
counterclockwise. The angle will be in range [-180, 180].
"""
return get_display_rotation(self)
@property
def interlaced_frame(self):
"""Is this frame an interlaced or progressive?"""
return bool(self.ptr.flags & lib.AV_FRAME_FLAG_INTERLACED)
@property
def pict_type(self):
"""Returns an integer that corresponds to the PictureType enum.
Wraps :ffmpeg:`AVFrame.pict_type`
:type: int
"""
return self.ptr.pict_type
@pict_type.setter
def pict_type(self, value):
self.ptr.pict_type = value
@property
def colorspace(self):
"""Colorspace of frame.
Wraps :ffmpeg:`AVFrame.colorspace`.
"""
return self.ptr.colorspace
@colorspace.setter
def colorspace(self, value):
self.ptr.colorspace = value
@property
def color_range(self):
"""Color range of frame.
Wraps :ffmpeg:`AVFrame.color_range`.
"""
return self.ptr.color_range
@color_range.setter
def color_range(self, value):
self.ptr.color_range = value
def reformat(self, *args, **kwargs):
"""reformat(width=None, height=None, format=None, src_colorspace=None, dst_colorspace=None, interpolation=None)
Create a new :class:`VideoFrame` with the given width/height/format/colorspace.
.. seealso:: :meth:`.VideoReformatter.reformat` for arguments.
"""
if not self.reformatter:
self.reformatter = VideoReformatter()
return self.reformatter.reformat(self, *args, **kwargs)
def to_rgb(self, **kwargs):
"""Get an RGB version of this frame.
Any ``**kwargs`` are passed to :meth:`.VideoReformatter.reformat`.
>>> frame = VideoFrame(1920, 1080)
>>> frame.format.name
'yuv420p'
>>> frame.to_rgb().format.name
'rgb24'
"""
return self.reformat(format="rgb24", **kwargs)
@cython.ccall
def save(self, filepath: object):
"""Save a VideoFrame as a JPG or PNG.
:param filepath: str | Path
"""
is_jpg: cython.bint
if filepath.endswith(".png"):
is_jpg = False
elif filepath.endswith(".jpg") or filepath.endswith(".jpeg"):
is_jpg = True
else:
raise ValueError("filepath must end with png or jpg.")
encoder: str = "mjpeg" if is_jpg else "png"
pix_fmt: str = "yuvj420p" if is_jpg else "rgb24"
from av.container.core import open
with open(filepath, "w", options={"update": "1"}) as output:
output_stream = output.add_stream(encoder, pix_fmt=pix_fmt)
output_stream.width = self.width
output_stream.height = self.height
output.mux(output_stream.encode(self.reformat(format=pix_fmt)))
output.mux(output_stream.encode(None))
def to_image(self, **kwargs):
"""Get an RGB ``PIL.Image`` of this frame.
Any ``**kwargs`` are passed to :meth:`.VideoReformatter.reformat`.
.. note:: PIL or Pillow must be installed.
"""
from PIL import Image
plane: VideoPlane = self.reformat(format="rgb24", **kwargs).planes[0]
i_buf: cython.const[uint8_t][:] = plane
i_pos: cython.size_t = 0
i_stride: cython.size_t = plane.line_size
o_pos: cython.size_t = 0
o_stride: cython.size_t = plane.width * 3
o_size: cython.size_t = plane.height * o_stride
o_buf: bytearray = bytearray(o_size)
while o_pos < o_size:
o_buf[o_pos : o_pos + o_stride] = i_buf[i_pos : i_pos + o_stride]
i_pos += i_stride
o_pos += o_stride
return Image.frombytes(
"RGB", (plane.width, plane.height), bytes(o_buf), "raw", "RGB", 0, 1
)
def to_ndarray(self, channel_last=False, **kwargs):
"""Get a numpy array of this frame.
Any ``**kwargs`` are passed to :meth:`.VideoReformatter.reformat`.
The array returned is generally of dimension (height, width, channels).
:param bool channel_last: If True, the shape of array will be
(height, width, channels) rather than (channels, height, width) for
the "yuv444p" and "yuvj444p" formats.
.. note:: Numpy must be installed.
.. note:: For formats which return an array of ``uint16``, ``float16`` or ``float32``,
the samples will be in the system's native byte order.
.. note:: For ``pal8``, an ``(image, palette)`` tuple will be returned,
with the palette being in ARGB (PyAV will swap bytes if needed).
.. note:: For ``gbrp`` formats, channels are flipped to RGB order.
"""
frame: VideoFrame = self.reformat(**kwargs)
import numpy as np
# check size
if frame.format.name in {"yuv420p", "yuvj420p", "yuyv422", "yuv422p10le"}:
assert frame.width % 2 == 0, (
"the width has to be even for this pixel format"
)
assert frame.height % 2 == 0, (
"the height has to be even for this pixel format"
)
# cases planes are simply concatenated in shape (height, width, channels)
itemsize, dtype = {
"abgr": (4, "uint8"),
"argb": (4, "uint8"),
"bayer_bggr8": (1, "uint8"),
"bayer_gbrg8": (1, "uint8"),
"bayer_grbg8": (1, "uint8"),
"bayer_rggb8": (1, "uint8"),
"bayer_bggr16le": (2, "uint16"),
"bayer_bggr16be": (2, "uint16"),
"bayer_gbrg16le": (2, "uint16"),
"bayer_gbrg16be": (2, "uint16"),
"bayer_grbg16le": (2, "uint16"),
"bayer_grbg16be": (2, "uint16"),
"bayer_rggb16le": (2, "uint16"),
"bayer_rggb16be": (2, "uint16"),
"bgr24": (3, "uint8"),
"bgr48be": (6, "uint16"),
"bgr48le": (6, "uint16"),
"bgr8": (1, "uint8"),
"bgra": (4, "uint8"),
"bgra64be": (8, "uint16"),
"bgra64le": (8, "uint16"),
"gbrap": (1, "uint8"),
"gbrap10be": (2, "uint16"),
"gbrap10le": (2, "uint16"),
"gbrap12be": (2, "uint16"),
"gbrap12le": (2, "uint16"),
"gbrap14be": (2, "uint16"),
"gbrap14le": (2, "uint16"),
"gbrap16be": (2, "uint16"),
"gbrap16le": (2, "uint16"),
"gbrapf32be": (4, "float32"),
"gbrapf32le": (4, "float32"),
"gbrp": (1, "uint8"),
"gbrp10be": (2, "uint16"),
"gbrp10le": (2, "uint16"),
"gbrp12be": (2, "uint16"),
"gbrp12le": (2, "uint16"),
"gbrp14be": (2, "uint16"),
"gbrp14le": (2, "uint16"),
"gbrp16be": (2, "uint16"),
"gbrp16le": (2, "uint16"),
"gbrp9be": (2, "uint16"),
"gbrp9le": (2, "uint16"),
"gbrpf32be": (4, "float32"),
"gbrpf32le": (4, "float32"),
"gray": (1, "uint8"),
"gray10be": (2, "uint16"),
"gray10le": (2, "uint16"),
"gray12be": (2, "uint16"),
"gray12le": (2, "uint16"),
"gray14be": (2, "uint16"),
"gray14le": (2, "uint16"),
"gray16be": (2, "uint16"),
"gray16le": (2, "uint16"),
"gray8": (1, "uint8"),
"gray9be": (2, "uint16"),
"gray9le": (2, "uint16"),
"grayf32be": (4, "float32"),
"grayf32le": (4, "float32"),
"rgb24": (3, "uint8"),
"rgb48be": (6, "uint16"),
"rgb48le": (6, "uint16"),
"rgb8": (1, "uint8"),
"rgba": (4, "uint8"),
"rgba64be": (8, "uint16"),
"rgba64le": (8, "uint16"),
"rgbaf16be": (8, "float16"),
"rgbaf16le": (8, "float16"),
"rgbaf32be": (16, "float32"),
"rgbaf32le": (16, "float32"),
"rgbf32be": (12, "float32"),
"rgbf32le": (12, "float32"),
"yuv444p": (1, "uint8"),
"yuv444p16be": (2, "uint16"),
"yuv444p16le": (2, "uint16"),
"yuva444p16be": (2, "uint16"),
"yuva444p16le": (2, "uint16"),
"yuvj444p": (1, "uint8"),
"yuyv422": (2, "uint8"),
}.get(frame.format.name, (None, None))
if itemsize is not None:
layers = [
useful_array(plan, itemsize, dtype).reshape(
frame.height, frame.width, -1
)
for plan in frame.planes
]
if len(layers) == 1: # shortcut, avoid memory copy
array = layers[0]
else: # general case
array = np.concatenate(layers, axis=2)
array = byteswap_array(array, frame.format.name.endswith("be"))
if array.shape[2] == 1: # skip last channel for gray images
return array.squeeze(2)
if frame.format.name.startswith("gbr"): # gbr -> rgb
buffer = array[:, :, 0].copy()
array[:, :, 0] = array[:, :, 2]
array[:, :, 2] = array[:, :, 1]
array[:, :, 1] = buffer
if not channel_last and frame.format.name in {"yuv444p", "yuvj444p"}:
array = np.moveaxis(array, 2, 0)
return array
# special cases
if frame.format.name in {"yuv420p", "yuvj420p"}:
return np.hstack(
[
useful_array(frame.planes[0]),
useful_array(frame.planes[1]),
useful_array(frame.planes[2]),
]
).reshape(-1, frame.width)
if frame.format.name == "yuv422p10le":
# Read planes as uint16 at their original width
y = useful_array(frame.planes[0], 2, "uint16").reshape(
frame.height, frame.width
)
u = useful_array(frame.planes[1], 2, "uint16").reshape(
frame.height, frame.width // 2
)
v = useful_array(frame.planes[2], 2, "uint16").reshape(
frame.height, frame.width // 2
)
# Double the width of U and V by repeating each value
u_full = np.repeat(u, 2, axis=1)
v_full = np.repeat(v, 2, axis=1)
if channel_last:
return np.stack([y, u_full, v_full], axis=2)
return np.stack([y, u_full, v_full], axis=0)
if frame.format.name == "pal8":
image = useful_array(frame.planes[0]).reshape(frame.height, frame.width)
palette = (
np.frombuffer(frame.planes[1], "i4")
.astype(">i4")
.reshape(-1, 1)
.view(np.uint8)
)
return image, palette
if frame.format.name == "nv12":
return np.hstack(
[
useful_array(frame.planes[0]),
useful_array(frame.planes[1], 2),
]
).reshape(-1, frame.width)
raise ValueError(
f"Conversion to numpy array with format `{frame.format.name}` is not yet supported"
)
def set_image(self, img):
"""
Update content from a ``PIL.Image``.
"""
if img.mode != "RGB":
img = img.convert("RGB")
copy_array_to_plane(img, self.planes[0], 3)
@staticmethod
def from_image(img):
"""
Construct a frame from a ``PIL.Image``.
"""
frame: VideoFrame = VideoFrame(img.size[0], img.size[1], "rgb24")
frame.set_image(img)
return frame
@staticmethod
def from_numpy_buffer(array, format="rgb24", width=0):
"""
Construct a frame from a numpy buffer.
:param int width: optional width of actual image, if different from the array width.
.. note:: For formats which expect an array of ``uint16``, ``float16`` or ``float32``,
the samples must be in the system's native byte order.
.. note:: for ``gbrp`` formats, channels are assumed to be given in RGB order.
.. note:: For formats where width of the array is not the same as the width of the image,
for example with yuv420p images the UV rows at the bottom have padding bytes in the middle of the
row as well as at the end. To cope with these, callers need to be able to pass the actual width.
"""
import numpy as np
height = array.shape[0]
if not width:
width = array.shape[1]
if format in {"rgb24", "bgr24"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (3, 1):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgb48le", "rgb48be", "bgr48le", "bgr48be"}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (6, 2):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgbf32le", "rgbf32be"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (12, 4):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgba", "bgra", "argb", "abgr"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (4, 1):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgba64le", "rgba64be", "bgra64le", "bgra64be"}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (8, 2):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgbaf16le", "rgbaf16be"}:
check_ndarray(array, "float16", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (8, 2):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"rgbaf32le", "rgbaf32be"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (16, 4):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {
"gray",
"gray8",
"rgb8",
"bgr8",
"bayer_bggr8",
"bayer_gbrg8",
"bayer_grbg8",
"bayer_rggb8",
}:
check_ndarray(array, "uint8", 2)
if array.strides[1] != 1:
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {
"gray9be",
"gray9le",
"gray10be",
"gray10le",
"gray12be",
"gray12le",
"gray14be",
"gray14le",
"gray16be",
"gray16le",
"bayer_bggr16be",
"bayer_bggr16le",
"bayer_gbrg16be",
"bayer_gbrg16le",
"bayer_grbg16be",
"bayer_grbg16le",
"bayer_rggb16be",
"bayer_rggb16le",
}:
check_ndarray(array, "uint16", 2)
if array.strides[1] != 2:
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"grayf32le", "grayf32be"}:
check_ndarray(array, "float32", 2)
if array.strides[1] != 4:
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (array.strides[0],)
elif format in {"gbrp"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (3, 1):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 3,
array.strides[0] // 3,
array.strides[0] // 3,
)
elif format in {
"gbrp9be",
"gbrp9le",
"gbrp10be",
"gbrp10le",
"gbrp12be",
"gbrp12le",
"gbrp14be",
"gbrp14le",
"gbrp16be",
"gbrp16le",
}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (6, 2):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 3,
array.strides[0] // 3,
array.strides[0] // 3,
)
elif format in {"gbrpf32be", "gbrpf32le"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 3)
if array.strides[1:] != (12, 4):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 3,
array.strides[0] // 3,
array.strides[0] // 3,
)
elif format in {"gbrap"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (4, 1):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
)
elif format in {
"gbrap10be",
"gbrap10le",
"gbrap12be",
"gbrap12le",
"gbrap14be",
"gbrap14le",
"gbrap16be",
"gbrap16le",
}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (8, 2):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
)
elif format in {"gbrapf32be", "gbrapf32le"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 4)
if array.strides[1:] != (16, 4):
raise ValueError("provided array does not have C_CONTIGUOUS rows")
linesizes = (
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
array.strides[0] // 4,
)
elif format in {"yuv420p", "yuvj420p", "nv12"}:
check_ndarray(array, "uint8", 2)
check_ndarray_shape(array, array.shape[0] % 3 == 0)
check_ndarray_shape(array, array.shape[1] % 2 == 0)
height = height // 6 * 4
if array.strides[1] != 1:
raise ValueError("provided array does not have C_CONTIGUOUS rows")
if format in {"yuv420p", "yuvj420p"}:
# For YUV420 planar formats, the UV plane stride is always half the Y stride.
linesizes = (
array.strides[0],
array.strides[0] // 2,
array.strides[0] // 2,
)
else:
# Planes where U and V are interleaved have the same stride as Y.
linesizes = (array.strides[0], array.strides[0])
else:
raise ValueError(
f"Conversion from numpy array with format `{format}` is not yet supported"
)
if format.startswith("gbrap"): # rgba -> gbra
array = np.ascontiguousarray(np.moveaxis(array[..., [1, 2, 0, 3]], -1, 0))
elif format.startswith("gbrp"): # rgb -> gbr
array = np.ascontiguousarray(np.moveaxis(array[..., [1, 2, 0]], -1, 0))
frame = VideoFrame(_cinit_bypass_sentinel)
frame._image_fill_pointers_numpy(array, width, height, linesizes, format)
return frame
def _image_fill_pointers_numpy(self, buffer, width, height, linesizes, format):
c_format: lib.AVPixelFormat
c_ptr: cython.pointer[uint8_t]
c_data: cython.size_t
# If you want to use the numpy notation, then you need to include the following lines at the top of the file:
# cimport numpy as cnp
# cnp.import_array()
# And add the numpy include directories to the setup.py files
# hint np.get_include()
# cdef cnp.ndarray[
# dtype=cnp.uint8_t, ndim=1,
# negative_indices=False, mode='c'] c_buffer
# c_buffer = buffer.reshape(-1)
# c_ptr = &c_buffer[0]
# c_ptr = <uint8_t*> (<void*>(buffer.ctypes.data))
# Using buffer.ctypes.data helps avoid any kind of usage of the c-api from
# numpy, which avoid the need to add numpy as a compile time dependency.
c_data = buffer.ctypes.data
c_ptr = cython.cast(cython.pointer[uint8_t], c_data)
c_format = get_pix_fmt(format)
lib.av_freep(cython.address(self._buffer))
# Hold on to a reference for the numpy buffer so that it doesn't get accidentally garbage collected
self._np_buffer = buffer
self.ptr.format = c_format
self.ptr.width = width
self.ptr.height = height
for i, linesize in enumerate(linesizes):
self.ptr.linesize[i] = linesize
res = lib.av_image_fill_pointers(
self.ptr.data,
cython.cast(lib.AVPixelFormat, self.ptr.format),
self.ptr.height,
c_ptr,
self.ptr.linesize,
)
if res:
err_check(res)
self._init_user_attributes()
@staticmethod
def from_ndarray(array, format="rgb24", channel_last=False):
"""
Construct a frame from a numpy array.
:param bool channel_last: If False (default), the shape for the yuv444p and yuvj444p
is given by (channels, height, width) rather than (height, width, channels).
.. note:: For formats which expect an array of ``uint16``, ``float16`` or ``float32``,
the samples must be in the system's native byte order.
.. note:: for ``pal8``, an ``(image, palette)`` pair must be passed. `palette` must
have shape (256, 4) and is given in ARGB format (PyAV will swap bytes if needed).
.. note:: for ``gbrp`` formats, channels are assumed to be given in RGB order.
"""
import numpy as np
# case layers are concatenated
channels, itemsize, dtype = {
"bayer_bggr16be": (1, 2, "uint16"),
"bayer_bggr16le": (1, 2, "uint16"),
"bayer_bggr8": (1, 1, "uint8"),
"bayer_gbrg16be": (1, 2, "uint16"),
"bayer_gbrg16le": (1, 2, "uint16"),
"bayer_gbrg8": (1, 1, "uint8"),
"bayer_grbg16be": (1, 2, "uint16"),
"bayer_grbg16le": (1, 2, "uint16"),
"bayer_grbg8": (1, 1, "uint8"),
"bayer_rggb16be": (1, 2, "uint16"),
"bayer_rggb16le": (1, 2, "uint16"),
"bayer_rggb8": (1, 1, "uint8"),
"bgr8": (1, 1, "uint8"),
"gbrap": (4, 1, "uint8"),
"gbrap10be": (4, 2, "uint16"),
"gbrap10le": (4, 2, "uint16"),
"gbrap12be": (4, 2, "uint16"),
"gbrap12le": (4, 2, "uint16"),
"gbrap14be": (4, 2, "uint16"),
"gbrap14le": (4, 2, "uint16"),
"gbrap16be": (4, 2, "uint16"),
"gbrap16le": (4, 2, "uint16"),
"gbrapf32be": (4, 4, "float32"),
"gbrapf32le": (4, 4, "float32"),
"gbrp": (3, 1, "uint8"),
"gbrp10be": (3, 2, "uint16"),
"gbrp10le": (3, 2, "uint16"),
"gbrp12be": (3, 2, "uint16"),
"gbrp12le": (3, 2, "uint16"),
"gbrp14be": (3, 2, "uint16"),
"gbrp14le": (3, 2, "uint16"),
"gbrp16be": (3, 2, "uint16"),
"gbrp16le": (3, 2, "uint16"),
"gbrp9be": (3, 2, "uint16"),
"gbrp9le": (3, 2, "uint16"),
"gbrpf32be": (3, 4, "float32"),
"gbrpf32le": (3, 4, "float32"),
"gray": (1, 1, "uint8"),
"gray10be": (1, 2, "uint16"),
"gray10le": (1, 2, "uint16"),
"gray12be": (1, 2, "uint16"),
"gray12le": (1, 2, "uint16"),
"gray14be": (1, 2, "uint16"),
"gray14le": (1, 2, "uint16"),
"gray16be": (1, 2, "uint16"),
"gray16le": (1, 2, "uint16"),
"gray8": (1, 1, "uint8"),
"gray9be": (1, 2, "uint16"),
"gray9le": (1, 2, "uint16"),
"grayf32be": (1, 4, "float32"),
"grayf32le": (1, 4, "float32"),
"rgb8": (1, 1, "uint8"),
"yuv444p": (3, 1, "uint8"),
"yuv444p16be": (3, 2, "uint16"),
"yuv444p16le": (3, 2, "uint16"),
"yuva444p16be": (4, 2, "uint16"),
"yuva444p16le": (4, 2, "uint16"),
"yuvj444p": (3, 1, "uint8"),
}.get(format, (None, None, None))
if channels is not None:
if array.ndim == 2: # (height, width) -> (height, width, 1)
array = array[:, :, None]
check_ndarray(array, dtype, 3)
if not channel_last and format in {"yuv444p", "yuvj444p"}:
array = np.moveaxis(array, 0, 2) # (channels, h, w) -> (h, w, channels)
check_ndarray_shape(array, array.shape[2] == channels)
array = byteswap_array(array, format.endswith("be"))
frame = VideoFrame(array.shape[1], array.shape[0], format)
if frame.format.name.startswith("gbr"): # rgb -> gbr
array = np.concatenate(
[ # not inplace to avoid bad surprises
array[:, :, 1:3],
array[:, :, 0:1],
array[:, :, 3:],
],
axis=2,
)
for i in range(channels):
copy_array_to_plane(array[:, :, i], frame.planes[i], itemsize)
return frame
# other cases
if format == "pal8":
array, palette = array
check_ndarray(array, "uint8", 2)
check_ndarray(palette, "uint8", 2)
check_ndarray_shape(palette, palette.shape == (256, 4))
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(array, frame.planes[0], 1)
frame.planes[1].update(palette.view(">i4").astype("i4").tobytes())
return frame
elif format in {"yuv420p", "yuvj420p"}:
check_ndarray(array, "uint8", 2)
check_ndarray_shape(array, array.shape[0] % 3 == 0)
check_ndarray_shape(array, array.shape[1] % 2 == 0)
frame = VideoFrame(array.shape[1], (array.shape[0] * 2) // 3, format)
u_start = frame.width * frame.height
v_start = 5 * u_start // 4
flat = array.reshape(-1)
copy_array_to_plane(flat[0:u_start], frame.planes[0], 1)
copy_array_to_plane(flat[u_start:v_start], frame.planes[1], 1)
copy_array_to_plane(flat[v_start:], frame.planes[2], 1)
return frame
elif format == "yuv422p10le":
if not isinstance(array, np.ndarray) or array.dtype != np.uint16:
raise ValueError("Array must be uint16 type")
# Convert to channel-first if needed
if channel_last and array.shape[2] == 3:
array = np.moveaxis(array, 2, 0)
elif not (array.shape[0] == 3):
raise ValueError(
"Array must have shape (3, height, width) or (height, width, 3)"
)
height, width = array.shape[1:]
if width % 2 != 0 or height % 2 != 0:
raise ValueError("Width and height must be even")
frame = VideoFrame(width, height, format)
copy_array_to_plane(array[0], frame.planes[0], 2)
# Subsample U and V by taking every other column
u = array[1, :, ::2].copy() # Need copy to ensure C-contiguous
v = array[2, :, ::2].copy() # Need copy to ensure C-contiguous
copy_array_to_plane(u, frame.planes[1], 2)
copy_array_to_plane(v, frame.planes[2], 2)
return frame
elif format == "yuyv422":
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[0] % 2 == 0)
check_ndarray_shape(array, array.shape[1] % 2 == 0)
check_ndarray_shape(array, array.shape[2] == 2)
elif format in {"rgb24", "bgr24"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 3)
elif format in {"argb", "rgba", "abgr", "bgra"}:
check_ndarray(array, "uint8", 3)
check_ndarray_shape(array, array.shape[2] == 4)
elif format in {"rgb48be", "rgb48le", "bgr48be", "bgr48le"}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 3)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
byteswap_array(array, format.endswith("be")), frame.planes[0], 6
)
return frame
elif format in {"rgbf32be", "rgbf32le"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 3)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
byteswap_array(array, format.endswith("be")), frame.planes[0], 12
)
return frame
elif format in {"rgba64be", "rgba64le", "bgra64be", "bgra64le"}:
check_ndarray(array, "uint16", 3)
check_ndarray_shape(array, array.shape[2] == 4)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
byteswap_array(array, format.endswith("be")), frame.planes[0], 8
)
return frame
elif format in {"rgbaf16be", "rgbaf16le"}:
check_ndarray(array, "float16", 3)
check_ndarray_shape(array, array.shape[2] == 4)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
byteswap_array(array, format.endswith("be")), frame.planes[0], 8
)
return frame
elif format in {"rgbaf32be", "rgbaf32le"}:
check_ndarray(array, "float32", 3)
check_ndarray_shape(array, array.shape[2] == 4)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
byteswap_array(array, format.endswith("be")), frame.planes[0], 16
)
return frame
elif format == "nv12":
check_ndarray(array, "uint8", 2)
check_ndarray_shape(array, array.shape[0] % 3 == 0)
check_ndarray_shape(array, array.shape[1] % 2 == 0)
frame = VideoFrame(array.shape[1], (array.shape[0] * 2) // 3, format)
uv_start = frame.width * frame.height
flat = array.reshape(-1)
copy_array_to_plane(flat[:uv_start], frame.planes[0], 1)
copy_array_to_plane(flat[uv_start:], frame.planes[1], 2)
return frame
else:
raise ValueError(
f"Conversion from numpy array with format `{format}` is not yet supported"
)
frame = VideoFrame(array.shape[1], array.shape[0], format)
copy_array_to_plane(
array, frame.planes[0], 1 if array.ndim == 2 else array.shape[2]
)
return frame
@staticmethod
def from_bytes(
img_bytes: bytes,
width: int,
height: int,
format="rgba",
flip_horizontal=False,
flip_vertical=False,
):
frame = VideoFrame(width, height, format)
if format == "rgba":
copy_bytes_to_plane(
img_bytes, frame.planes[0], 4, flip_horizontal, flip_vertical
)
elif format in {
"bayer_bggr8",
"bayer_rggb8",
"bayer_gbrg8",
"bayer_grbg8",
"bayer_bggr16le",
"bayer_rggb16le",
"bayer_gbrg16le",
"bayer_grbg16le",
"bayer_bggr16be",
"bayer_rggb16be",
"bayer_gbrg16be",
"bayer_grbg16be",
}:
copy_bytes_to_plane(
img_bytes,
frame.planes[0],
1 if format.endswith("8") else 2,
flip_horizontal,
flip_vertical,
)
else:
raise NotImplementedError(f"Format '{format}' is not supported.")
return frame