env_gptq3/lib/python3.12/site-packages/gptqmodel/utils/image.py

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# Licensed under the Apache License, Version 2.0 (the "License");
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#     http://www.apache.org/licenses/LICENSE-2.0
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import base64
from io import BytesIO

import requests
from PIL import Image


def extract_vision_info(conversations: list[dict] | list[list[dict]]) -> list[dict]:
    vision_infos = []
    if isinstance(conversations[0], dict):
        conversations = [conversations]
    for conversation in conversations:
        for message in conversation:
            if isinstance(message["content"], list):
                for ele in message["content"]:
                    if (
                            "image" in ele
                            or "image_url" in ele
                            or "video" in ele
                            or ele["type"] in ("image", "image_url", "video")
                    ):
                        vision_infos.append(ele)
    return vision_infos


def fetch_image(ele: dict[str, str | Image.Image]) -> Image.Image:
    if "image" in ele:
        image = ele["image"]
    else:
        image = ele["image_url"]
    image_obj = None
    if isinstance(image, Image.Image):
        image_obj = image
    elif image.startswith("http://") or image.startswith("https://"):
        image_obj = Image.open(requests.get(image, stream=True).raw)
    elif image.startswith("file://"):
        image_obj = Image.open(image[7:])
    elif image.startswith("data:image"):
        if "base64," in image:
            _, base64_data = image.split("base64,", 1)
            data = base64.b64decode(base64_data)
            image_obj = Image.open(BytesIO(data))
    else:
        image_obj = Image.open(image)
    if image_obj is None:
        raise ValueError(f"Unrecognized image input, support local path, http url, base64 and PIL.Image, got {image}")
    return image_obj