demo/meta.py

# -*- coding: utf-8 -*-

# ===========================================================================================
#
#    Copyright (c) Beijing Academy of Artificial Intelligence (BAAI). All rights reserved.
#
#    Author        : Fan Zhang
#    Email         : [email protected]
#    Institute     : Beijing Academy of Artificial Intelligence (BAAI)
#    Create On     : 2023-12-12 02:54
#    Last Modified : 2023-12-20 14:27
#    File Name     : meta.py
#    Description   :
#
# ===========================================================================================

import base64
from dataclasses import dataclass, field
import io
from enum import Enum
from PIL import Image
from typing import List, Tuple

import cv2
import numpy as np

from .constants import EVA_IMAGE_SIZE, GRD_SYMBOL, BOP_SYMBOL, EOP_SYMBOL, BOO_SYMBOL, EOO_SYMBOL
from .constants import DEFAULT_VIDEO_TOKEN, DEFAULT_EOS_TOKEN, USER_TOKEN, ASSISTANT_TOKEN, FAKE_VIDEO_END_TOKEN

from .utils import gen_id, frontend_logger as logging


class Role(Enum):
    UNKNOWN = 0,
    USER = 1,
    ASSISTANT = 2,


class DataType(Enum):
    UNKNOWN = 0,
    TEXT = 1,
    IMAGE = 2,
    GROUNDING = 3,
    VIDEO = 4,
    ERROR = 5,


@dataclass
class DataMeta:
    datatype: DataType = DataType.UNKNOWN
    text: str = None
    image: Image.Image = None
    mask: Image.Image = None
    coordinate: List[int] = None
    frames: List[Image.Image] = None
    stack_frame: Image.Image = None

    @property
    def grounding(self):
        return self.coordinate is not None

    @property
    def text_str(self):
        return self.text

    @property
    def image_str(self):
        return self.image2str(self.image)

    @property
    def video_str(self):
        ret = f'<div style="overflow:scroll"><b>[VIDEO]</b></div>{self.image2str(self.stack_frame)}'
        return ret

    @property
    def grounding_str(self):
        ret = ""
        if self.text is not None:
            ret += f'<div style="overflow:scroll"><b>[PHRASE]</b>{self.text}</div>'

        ret += self.image2str(self.mask)

        if self.image is not None:
            ret += self.image2str(self.image)
        return ret

    def image2str(self, image):
        buf = io.BytesIO()
        image.save(buf, format="WEBP")
        i_str = base64.b64encode(buf.getvalue()).decode()
        return f'<div style="float:left"><img src="data:image/png;base64, {i_str}"></div>'

    def format_chatbot(self):
        match self.datatype:
            case DataType.TEXT | DataType.ERROR:
                return self.text_str
            case DataType.IMAGE:
                return self.image_str
            case DataType.VIDEO:
                return self.video_str
            case DataType.GROUNDING:
                return self.grounding_str
            case _:
                return ""

    def format_prompt(self) -> List[str | Image.Image]:
        match self.datatype:
            case DataType.TEXT:
                return [self.text]
            case DataType.IMAGE:
                return [self.image]
            case DataType.VIDEO:
                return [DEFAULT_VIDEO_TOKEN] + self.frames + [FAKE_VIDEO_END_TOKEN]
            case DataType.GROUNDING:
                ret = []
                if self.text is not None:
                    ret.append(f"{BOP_SYMBOL}{self.text}{EOP_SYMBOL}")
                ret += [BOO_SYMBOL, self.mask, EOO_SYMBOL]
                if self.image is not None:
                    ret.append(self.image)
                return ret
            case _:
                return []

    def __str__(self):
        s = ""
        if self.text is not None:
            s += f"T:{self.text}"

        if self.image is not None:
            w, h = self.image.size
            s += f"[I:{h}x{w}]"

        if self.coordinate is not None:
            l, t, r, b = self.coordinate
            s += f"[C:({l:03d},{t:03d}),({r:03d},{b:03d})]"

        if self.frames is not None:
            w, h = self.frames[0].size
            s += f"[V:{len(self.frames)}x{h}x{w}]"

        return s

    @classmethod
    def build(cls, text=None, image=None, coordinate=None, frames=None, is_error=False, *, resize: bool = True):
        ins = cls()
        ins.text = text if text != "" else None
        # ins.image = cls.resize(image, force=resize)
        ins.image = image
        ins.coordinate = cls.fix(coordinate)
        # ins.frames = cls.resize(frames, force=resize)
        ins.frames = frames

        if is_error:
            ins.datatype = DataType.ERROR
        elif coordinate is not None:
            ins.datatype = DataType.GROUNDING
            ins.draw_box()
        elif image is not None:
            ins.datatype = DataType.IMAGE
        elif text is not None:
            ins.datatype = DataType.TEXT
        else:
            ins.datatype = DataType.VIDEO
            ins.stack()

        return ins

    @classmethod
    def fix(cls, coordinate):
        if coordinate is None:
            return None

        l, t, r, b = coordinate
        l = min(EVA_IMAGE_SIZE, max(0, l))
        t = min(EVA_IMAGE_SIZE, max(0, t))
        r = min(EVA_IMAGE_SIZE, max(0, r))
        b = min(EVA_IMAGE_SIZE, max(0, b))
        return min(l, r), min(t, b), max(l, r), max(t, b)

    @classmethod
    def resize(cls, image: Image.Image | List[Image.Image] | None, *, force: bool = True):
        if image is None:
            return None

        if not force:
            return image

        if isinstance(image, Image.Image):
            image = [image]

        for idx, im in enumerate(image):
            w, h = im.size
            if w < h:
                h = int(EVA_IMAGE_SIZE / w * h)
                w = EVA_IMAGE_SIZE
            else:
                w = int(EVA_IMAGE_SIZE / h * w)
                h = EVA_IMAGE_SIZE

            image[idx] = im.resize((w, h))

        return image if len(image) > 1 else image[0]

    def draw_box(self):
        left, top, right, bottom = self.coordinate
        mask = np.zeros((EVA_IMAGE_SIZE, EVA_IMAGE_SIZE, 3), dtype=np.uint8)
        mask = cv2.rectangle(mask, (left, top), (right, bottom), (255, 255, 255), 3)
        self.mask = Image.fromarray(mask)

    def stack(self):
        w, h = self.frames[0].size
        n = len(self.frames)
        stack_frame = Image.new(mode="RGB", size=(w*n, h))
        for idx, f in enumerate(self.frames):
            stack_frame.paste(f, (idx*w, 0))
        self.stack_frame = stack_frame


class ConvMeta:

    def __init__(self):
        self.system: str = "You are a helpful assistant, dedicated to delivering comprehensive and meticulous responses."
        self.message: List[Tuple[Role, DataMeta]] = []
        self.log_id: str = gen_id()

        logging.info(f"{self.log_id}: create new round of chat")

    def append(self, r: Role, p: DataMeta):
        logging.info(f"{self.log_id}: APPEND [{r.name}] prompt element, type: {p.datatype.name}, message: {p}")
        self.message.append((r, p))

    def format_chatbot(self):
        ret = []
        for r, p in self.message:
            cur_p = p.format_chatbot()
            if r == Role.USER:
                ret.append((cur_p, None))
            else:
                ret.append((None, cur_p))
        return ret

    def format_prompt(self):
        ret = []
        has_coor = False
        for _, p in self.message:
            has_coor |= (p.datatype == DataType.GROUNDING)
            ret += p.format_prompt()

        if has_coor:
            ret.insert(0, GRD_SYMBOL)

        logging.info(f"{self.log_id}: format generation prompt: {ret}")
        return ret

    def format_chat(self):
        ret = [self.system]

        prev_r = None
        for r, p in self.message:
            if prev_r != r:
                if prev_r == Role.ASSISTANT:
                    ret.append(f"{DEFAULT_EOS_TOKEN}{USER_TOKEN}: ")
                elif prev_r is None:
                    ret.append(f" {USER_TOKEN}: ")
                else:
                    ret.append(f" {ASSISTANT_TOKEN}: ")
                ret += p.format_prompt()
                prev_r = r
            else:
                ret += p.format_prompt()

        ret.append(f" {ASSISTANT_TOKEN}:")

        logging.info(f"{self.log_id}: format chat prompt: {ret}")
        return ret

    def clear(self):
        logging.info(f"{self.log_id}: clear chat history, end current chat round.")
        del self.message
        self.message = []
        self.log_id = gen_id()

    def pop(self):
        if self.has_gen:
            logging.info(f"{self.log_id}: pop out previous generation / chat result")
            self.message.pop()

    def pop_error(self):
        new_message = []
        for r, p in self.message:
            if p.datatype == DataType.ERROR:
                logging.info(f"{self.log_id}: pop error message: {p.text_str}")
            else:
                new_message.append((r, p))
        del self.message
        self.message = new_message

    @property
    def has_gen(self):
        if len(self.message) == 0:
            return False
        if self.message[-1][0] == Role.USER:
            return False
        return True