import io

import random

import struct

import tempfile

from contextlib import contextmanager

from typing import List, Optional, Union

import numpy as np

import PIL.Image

import PIL.ImageOps

from .import_utils import BACKENDS_MAPPING, is_imageio_available, is_opencv_available

from .logging import get_logger

global_rng = random.Random()

logger = get_logger(__name__)

@contextmanager

def buffered_writer(raw_f):

f = io.BufferedWriter(raw_f)

yield f

f.flush()

def export_to_gif(image: List[PIL.Image.Image], output_gif_path: str = None, fps: int = 10) -> str:

if output_gif_path is None:

output_gif_path = tempfile.NamedTemporaryFile(suffix=".gif").name

image[0].save(

output_gif_path,

save_all=True,

append_images=image[1:],

optimize=False,

duration=1000 // fps,

loop=0,

)

return output_gif_path

def export_to_ply(mesh, output_ply_path: str = None):

"""

Write a PLY file for a mesh.

"""

if output_ply_path is None:

output_ply_path = tempfile.NamedTemporaryFile(suffix=".ply").name

coords = mesh.verts.detach().cpu().numpy()

faces = mesh.faces.cpu().numpy()

rgb = np.stack([mesh.vertex_channels[x].detach().cpu().numpy() for x in "RGB"], axis=1)

with buffered_writer(open(output_ply_path, "wb")) as f:

f.write(b"ply\n")

f.write(b"format binary_little_endian 1.0\n")

f.write(bytes(f"element vertex {len(coords)}\n", "ascii"))

f.write(b"property float x\n")

f.write(b"property float y\n")

f.write(b"property float z\n")

if rgb is not None:

f.write(b"property uchar red\n")

f.write(b"property uchar green\n")

f.write(b"property uchar blue\n")

if faces is not None:

f.write(bytes(f"element face {len(faces)}\n", "ascii"))

f.write(b"property list uchar int vertex_index\n")

f.write(b"end_header\n")

if rgb is not None:

rgb = (rgb * 255.499).round().astype(int)

vertices = [

(*coord, *rgb)

for coord, rgb in zip(

coords.tolist(),

rgb.tolist(),

)

]

format = struct.Struct("<3f3B")

for item in vertices:

f.write(format.pack(*item))

else:

format = struct.Struct("<3f")

for vertex in coords.tolist():

f.write(format.pack(*vertex))

if faces is not None:

format = struct.Struct("<B3I")

for tri in faces.tolist():

f.write(format.pack(len(tri), *tri))

return output_ply_path

def export_to_obj(mesh, output_obj_path: str = None):

if output_obj_path is None:

output_obj_path = tempfile.NamedTemporaryFile(suffix=".obj").name

verts = mesh.verts.detach().cpu().numpy()

faces = mesh.faces.cpu().numpy()

vertex_colors = np.stack([mesh.vertex_channels[x].detach().cpu().numpy() for x in "RGB"], axis=1)

vertices = [

"{} {} {} {} {} {}".format(*coord, *color) for coord, color in zip(verts.tolist(), vertex_colors.tolist())

]

faces = ["f {} {} {}".format(str(tri[0] + 1), str(tri[1] + 1), str(tri[2] + 1)) for tri in faces.tolist()]

combined_data = ["v " + vertex for vertex in vertices] + faces

with open(output_obj_path, "w") as f:

f.writelines("\n".join(combined_data))

def _legacy_export_to_video(

video_frames: Union[List[np.ndarray], List[PIL.Image.Image]], output_video_path: str = None, fps: int = 10

):

if is_opencv_available():

import cv2

else:

raise ImportError(BACKENDS_MAPPING["opencv"][1].format("export_to_video"))

if output_video_path is None:

output_video_path = tempfile.NamedTemporaryFile(suffix=".mp4").name

if isinstance(video_frames[0], np.ndarray):

video_frames = [(frame * 255).astype(np.uint8) for frame in video_frames]

elif isinstance(video_frames[0], PIL.Image.Image):

video_frames = [np.array(frame) for frame in video_frames]

fourcc = cv2.VideoWriter_fourcc(*"mp4v")

h, w, c = video_frames[0].shape

video_writer = cv2.VideoWriter(output_video_path, fourcc, fps=fps, frameSize=(w, h))

for i in range(len(video_frames)):

img = cv2.cvtColor(video_frames[i], cv2.COLOR_RGB2BGR)

video_writer.write(img)

return output_video_path

def export_to_video(

video_frames: Union[List[np.ndarray], List[PIL.Image.Image]],

output_video_path: str = None,

fps: int = 10,

quality: float = 5.0,

bitrate: Optional[int] = None,

macro_block_size: Optional[int] = 16,

) -> str:

"""

quality:

Video output quality. Default is 5. Uses variable bit rate. Highest quality is 10, lowest is 0. Set to None to

prevent variable bitrate flags to FFMPEG so you can manually specify them using output_params instead.

Specifying a fixed bitrate using `bitrate` disables this parameter.

bitrate:

Set a constant bitrate for the video encoding. Default is None causing `quality` parameter to be used instead.

Better quality videos with smaller file sizes will result from using the `quality` variable bitrate parameter

rather than specifying a fixed bitrate with this parameter.

macro_block_size:

Size constraint for video. Width and height, must be divisible by this number. If not divisible by this number

imageio will tell ffmpeg to scale the image up to the next closest size divisible by this number. Most codecs

are compatible with a macroblock size of 16 (default), some can go smaller (4, 8). To disable this automatic

feature set it to None or 1, however be warned many players can't decode videos that are odd in size and some

codecs will produce poor results or fail. See https://en.wikipedia.org/wiki/Macroblock.

"""

# TODO: Dhruv. Remove by Diffusers release 0.33.0

# Added to prevent breaking existing code

if not is_imageio_available():

logger.warning(

(

"It is recommended to use `export_to_video` with `imageio` and `imageio-ffmpeg` as a backend. \n"

"These libraries are not present in your environment. Attempting to use legacy OpenCV backend to export video. \n"

"Support for the OpenCV backend will be deprecated in a future Diffusers version"

)

)

return _legacy_export_to_video(video_frames, output_video_path, fps)

if is_imageio_available():

import imageio

else:

raise ImportError(BACKENDS_MAPPING["imageio"][1].format("export_to_video"))

try:

imageio.plugins.ffmpeg.get_exe()

except AttributeError:

raise AttributeError(

(

"Found an existing imageio backend in your environment. Attempting to export video with imageio. \n"

"Unable to find a compatible ffmpeg installation in your environment to use with imageio. Please install via `pip install imageio-ffmpeg"

)

)

if output_video_path is None:

output_video_path = tempfile.NamedTemporaryFile(suffix=".mp4").name

if isinstance(video_frames[0], np.ndarray):

video_frames = [(frame * 255).astype(np.uint8) for frame in video_frames]

elif isinstance(video_frames[0], PIL.Image.Image):

video_frames = [np.array(frame) for frame in video_frames]

with imageio.get_writer(

output_video_path, fps=fps, quality=quality, bitrate=bitrate, macro_block_size=macro_block_size

) as writer:

for frame in video_frames:

writer.append_data(frame)

return output_video_path