35 lines
1.0 KiB
Python
35 lines
1.0 KiB
Python
|
# SPDX-License-Identifier: Apache-2.0
|
||
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||
|
|
|
||
|
|
from dataclasses import dataclass
|
||
|
|
from typing import Literal
|
||
|
|
|
||
|
|
import torch
|
||
|
|
from PIL import Image
|
||
|
|
|
||
|
|
from .base import get_vllm_public_assets
|
||
|
|
|
||
|
|
VLM_IMAGES_DIR = "vision_model_images"
|
||
|
|
|
||
|
|
ImageAssetName = Literal["stop_sign", "cherry_blossom"]
|
||
|
|
|
||
|
|
|
||
|
|
@dataclass(frozen=True)
|
||
|
|
class ImageAsset:
|
||
|
|
name: ImageAssetName
|
||
|
|
|
||
|
|
@property
|
||
|
|
def pil_image(self) -> Image.Image:
|
||
|
|
image_path = get_vllm_public_assets(filename=f"{self.name}.jpg",
|
||
|
|
s3_prefix=VLM_IMAGES_DIR)
|
||
|
|
return Image.open(image_path)
|
||
|
|
|
||
|
|
@property
|
||
|
|
def image_embeds(self) -> torch.Tensor:
|
||
|
|
"""
|
||
|
|
Image embeddings, only used for testing purposes with llava 1.5.
|
||
|
|
"""
|
||
|
|
image_path = get_vllm_public_assets(filename=f"{self.name}.pt",
|
||
|
|
s3_prefix=VLM_IMAGES_DIR)
|
||
|
|
return torch.load(image_path, map_location="cpu", weights_only=True)
|