mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2026-01-11 02:04:28 +08:00
97 lines
2.9 KiB
Python
97 lines
2.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import base64
|
|
from io import BytesIO
|
|
from pathlib import Path
|
|
|
|
import torch
|
|
from PIL import Image
|
|
|
|
from .base import MediaIO
|
|
|
|
|
|
def rescale_image_size(image: Image.Image,
|
|
size_factor: float,
|
|
transpose: int = -1) -> Image.Image:
|
|
"""Rescale the dimensions of an image by a constant factor."""
|
|
new_width = int(image.width * size_factor)
|
|
new_height = int(image.height * size_factor)
|
|
image = image.resize((new_width, new_height))
|
|
if transpose >= 0:
|
|
image = image.transpose(Image.Transpose(transpose))
|
|
return image
|
|
|
|
|
|
# TODO: Support customizable background color to fill in.
|
|
def rgba_to_rgb(
|
|
image: Image.Image, background_color=(255, 255, 255)) -> Image.Image:
|
|
"""Convert an RGBA image to RGB with filled background color."""
|
|
assert image.mode == "RGBA"
|
|
converted = Image.new("RGB", image.size, background_color)
|
|
converted.paste(image, mask=image.split()[3]) # 3 is the alpha channel
|
|
return converted
|
|
|
|
|
|
def convert_image_mode(image: Image.Image, to_mode: str):
|
|
if image.mode == to_mode:
|
|
return image
|
|
elif image.mode == "RGBA" and to_mode == "RGB":
|
|
return rgba_to_rgb(image)
|
|
else:
|
|
return image.convert(to_mode)
|
|
|
|
|
|
class ImageMediaIO(MediaIO[Image.Image]):
|
|
|
|
def __init__(self, *, image_mode: str = "RGB") -> None:
|
|
super().__init__()
|
|
|
|
self.image_mode = image_mode
|
|
|
|
def load_bytes(self, data: bytes) -> Image.Image:
|
|
image = Image.open(BytesIO(data))
|
|
image.load()
|
|
return convert_image_mode(image, self.image_mode)
|
|
|
|
def load_base64(self, media_type: str, data: str) -> Image.Image:
|
|
return self.load_bytes(base64.b64decode(data))
|
|
|
|
def load_file(self, filepath: Path) -> Image.Image:
|
|
image = Image.open(filepath)
|
|
image.load()
|
|
return convert_image_mode(image, self.image_mode)
|
|
|
|
def encode_base64(
|
|
self,
|
|
media: Image.Image,
|
|
*,
|
|
image_format: str = "JPEG",
|
|
) -> str:
|
|
image = media
|
|
|
|
with BytesIO() as buffer:
|
|
image = convert_image_mode(image, self.image_mode)
|
|
image.save(buffer, image_format)
|
|
data = buffer.getvalue()
|
|
|
|
return base64.b64encode(data).decode('utf-8')
|
|
|
|
|
|
class ImageEmbeddingMediaIO(MediaIO[torch.Tensor]):
|
|
|
|
def __init__(self) -> None:
|
|
super().__init__()
|
|
|
|
def load_bytes(self, data: bytes) -> torch.Tensor:
|
|
buffer = BytesIO(data)
|
|
return torch.load(buffer, weights_only=True)
|
|
|
|
def load_base64(self, media_type: str, data: str) -> torch.Tensor:
|
|
return self.load_bytes(base64.b64decode(data))
|
|
|
|
def load_file(self, filepath: Path) -> torch.Tensor:
|
|
return torch.load(filepath, weights_only=True)
|
|
|
|
def encode_base64(self, media: torch.Tensor) -> str:
|
|
return base64.b64encode(media.numpy()).decode('utf-8')
|