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import io

import random

import struct

import tempfile

from contextlib import contextmanager

from typing import List, 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

) -> str:

# 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) as writer:

for frame in video_frames:

writer.append_data(frame)

return output_video_path