Spaces:
Running
Running
update
Browse files- app.py +42 -1
- img_utils.py +0 -233
app.py
CHANGED
@@ -4,13 +4,54 @@ import base64
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import os
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from PIL import Image, ImageDraw
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from io import BytesIO
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from img_utils import smart_resize
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import backoff
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import httpx
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from loguru import logger
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import time
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from typing import List, Optional
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import traceback
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def image_to_base64(image):
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buffered = BytesIO()
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import os
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from PIL import Image, ImageDraw
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from io import BytesIO
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import backoff
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import httpx
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from loguru import logger
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import time
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from typing import List, Optional
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import traceback
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import math
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def smart_resize(
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height: int,
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width: int,
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factor: int = 28,
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min_pixels: int = 3136,
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max_pixels: int = 12845056,
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max_aspect_ratio_allowed: float | None = None,
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size_can_be_smaller_than_factor: bool = False,
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):
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"""Rescales the image so that the following conditions are met:
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1. Both dimensions (height and width) are divisible by 'factor'.
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2. The total number of pixels is within the range ['min_pixels', 'max_pixels'].
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3. The aspect ratio of the image is maintained as closely as possible.
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"""
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if not size_can_be_smaller_than_factor and (height < factor or width < factor):
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raise ValueError(
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f"height:{height} or width:{width} must be larger than factor:{factor} "
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f"(when size_can_be_smaller_than_factor is False)"
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)
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elif max_aspect_ratio_allowed is not None and max(height, width) / min(height, width) > max_aspect_ratio_allowed:
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raise ValueError(
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f"absolute aspect ratio must be smaller than {max_aspect_ratio_allowed}, "
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f"got {max(height, width) / min(height, width)}"
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f"(when max_aspect_ratio_allowed is not None)"
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)
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h_bar = max(1, round(height / factor)) * factor
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w_bar = max(1, round(width / factor)) * factor
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if h_bar * w_bar > max_pixels:
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beta = math.sqrt((height * width) / max_pixels)
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h_bar = max(1, math.floor(height / beta / factor)) * factor
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w_bar = max(1, math.floor(width / beta / factor)) * factor
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elif h_bar * w_bar < min_pixels:
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beta = math.sqrt(min_pixels / (height * width))
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h_bar = math.ceil(height * beta / factor) * factor
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w_bar = math.ceil(width * beta / factor) * factor
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return h_bar, w_bar
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def image_to_base64(image):
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buffered = BytesIO()
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img_utils.py
DELETED
@@ -1,233 +0,0 @@
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import math
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from typing import List, Union, Dict, Any
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def round_by_factor(number: int, factor: int) -> int:
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"""返回最接近 number 的且能被 factor 整除的整数"""
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return round(number / factor) * factor
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def ceil_by_factor(number: int, factor: int) -> int:
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"""返回大于等于 number 的且能被 factor 整除的整数"""
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return math.ceil(number / factor) * factor
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def floor_by_factor(number: int, factor: int) -> int:
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"""返回小于等于 number 的且能被 factor 整除的整数"""
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return math.floor(number / factor) * factor
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def smart_resize(height, width, factor=28, min_pixels=56 * 56, max_pixels=14 * 14 * 4 * 1280, max_long_side=8192):
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"""缩放后图片满足以下条件:
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1. 长宽能被 factor 整除
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2. pixels 总数被限制在 [min_pixels, max_pixels] 内
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3. 最长边限制在 max_long_side 内
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4. 保证其长宽比基本不变
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"""
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if height < 2 or width < 2:
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raise ValueError(f"height:{height} or width:{width} must be larger than factor:{factor}")
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elif max(height, width) / min(height, width) > 200:
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raise ValueError(f"absolute aspect ratio must be smaller than 100, got {height} / {width}")
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if max(height, width) > max_long_side:
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beta = max(height, width) / max_long_side
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height, width = int(height / beta), int(width / beta)
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h_bar = round_by_factor(height, factor)
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w_bar = round_by_factor(width, factor)
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if h_bar * w_bar > max_pixels:
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beta = math.sqrt((height * width) / max_pixels)
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h_bar = floor_by_factor(height / beta, factor)
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w_bar = floor_by_factor(width / beta, factor)
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elif h_bar * w_bar < min_pixels:
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beta = math.sqrt(min_pixels / (height * width))
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h_bar = ceil_by_factor(height * beta, factor)
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w_bar = ceil_by_factor(width * beta, factor)
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return h_bar, w_bar
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def update_image_size_(image_ele: dict, min_tokens=1, max_tokens=12800, merge_base=2, patch_size=14):
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"""根据 min_tokens, max_tokens 更新 image_ele 的尺寸信息
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Args:
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image_ele (dict):
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- image_ele["image"]: str 图片路径
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- image_ele["height"]: int 图片原始高度
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- image_ele["width"]: int 图片原始宽度
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Returns:
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更新后的 image_ele, 新增如下 key-value pair
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dict:
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- image_ele["resized_height"]: int 输入到模型的真实高度
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- image_ele["resized_width"]: int 输入到模型的真实宽度
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- image_ele["seq_len"]: int 输入到模型所占的序列长度
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"""
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height, width = image_ele["height"], image_ele["width"]
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pixels_per_token = patch_size * patch_size * merge_base * merge_base
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resized_height, resized_width = smart_resize(
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height,
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width,
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factor=merge_base * patch_size,
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min_pixels=pixels_per_token * min_tokens,
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max_pixels=pixels_per_token * max_tokens,
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max_long_side=50000,
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)
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image_ele.update(
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{
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"resized_height": resized_height,
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"resized_width": resized_width,
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"seq_len": resized_height * resized_width // pixels_per_token + 2,
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}
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)
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return image_ele
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def _convert_bbox_format_from_abs_origin(bbox, image_ele: dict, *, tgt_format: str):
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x1, y1, x2, y2 = bbox
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if tgt_format == "abs_origin":
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new_bbox = [int(x1), int(y1), int(x2), int(y2)]
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elif tgt_format == "abs_resized":
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new_bbox = [
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int(x1 / image_ele["width"] * image_ele["resized_width"]),
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int(y1 / image_ele["height"] * image_ele["resized_height"]),
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int(x2 / image_ele["width"] * image_ele["resized_width"]),
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int(y2 / image_ele["height"] * image_ele["resized_height"]),
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]
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elif tgt_format == "qwen-vl":
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new_bbox = [
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int(x1 / image_ele["width"] * 999),
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int(y1 / image_ele["height"] * 999),
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int(x2 / image_ele["width"] * 999),
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int(y2 / image_ele["height"] * 999),
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]
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elif tgt_format == "rel":
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new_bbox = [
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float(x1 / image_ele["width"]),
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float(y1 / image_ele["height"]),
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float(x2 / image_ele["width"]),
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float(y2 / image_ele["height"]),
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]
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elif tgt_format == "molmo":
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new_bbox = [
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round(x1 / image_ele["width"] * 100, ndigits=1),
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round(y1 / image_ele["height"] * 100, ndigits=1),
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round(x2 / image_ele["width"] * 100, ndigits=1),
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round(y2 / image_ele["height"] * 100, ndigits=1),
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]
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else:
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assert False, f"Unknown tgt_format: {tgt_format}"
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return new_bbox
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def _convert_bbox_format_to_abs_origin(bbox, image_ele: dict, *, src_format: str):
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x1, y1, x2, y2 = bbox
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if src_format == "abs_origin":
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new_bbox = [int(x1), int(y1), int(x2), int(y2)]
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elif src_format == "abs_resized":
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new_bbox = [
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int(x1 / image_ele["resized_width"] * image_ele["width"]),
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int(y1 / image_ele["resized_height"] * image_ele["height"]),
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int(x2 / image_ele["resized_width"] * image_ele["width"]),
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int(y2 / image_ele["resized_height"] * image_ele["height"]),
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]
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elif src_format == "qwen-vl":
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new_bbox = [
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int(x1 / 999 * image_ele["width"]),
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int(y1 / 999 * image_ele["height"]),
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int(x2 / 999 * image_ele["width"]),
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int(y2 / 999 * image_ele["height"]),
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]
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elif src_format == "rel":
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new_bbox = [
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int(x1 * image_ele["width"]),
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int(y1 * image_ele["height"]),
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int(x2 * image_ele["width"]),
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int(y2 * image_ele["height"]),
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]
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elif src_format == "molmo":
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new_bbox = [
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int(x1 / 100 * image_ele["width"]),
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int(y1 / 100 * image_ele["height"]),
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int(x2 / 100 * image_ele["width"]),
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int(y2 / 100 * image_ele["height"]),
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]
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else:
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assert False, f"Unknown src_format: {src_format}"
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return new_bbox
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def convert_bbox_format(bbox, image_ele: dict, *, src_format: str, tgt_format: str):
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bbox_abs_origin = _convert_bbox_format_to_abs_origin(bbox, image_ele, src_format=src_format)
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bbox_tgt_format = _convert_bbox_format_from_abs_origin(bbox_abs_origin, image_ele, tgt_format=tgt_format)
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return bbox_tgt_format
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-
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def _convert_point_format_from_abs_origin(point, image_ele: dict, *, tgt_format: str):
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x, y = point
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if tgt_format == "abs_origin":
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new_point = [int(x), int(y)]
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elif tgt_format == "abs_resized":
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new_point = [
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int(x / image_ele["width"] * image_ele["resized_width"]),
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int(y / image_ele["height"] * image_ele["resized_height"]),
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]
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elif tgt_format == "qwen-vl":
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new_point = [
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int(x / image_ele["width"] * 999),
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int(y / image_ele["height"] * 999),
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]
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elif tgt_format == "rel":
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new_point = [
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float(x / image_ele["width"]),
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float(y / image_ele["height"]),
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]
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elif tgt_format == "molmo":
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new_point = [
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round(x / image_ele["width"] * 100, ndigits=1),
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round(y / image_ele["height"] * 100, ndigits=1),
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]
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else:
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assert False, f"Unknown tgt_format: {tgt_format}"
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return new_point
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-
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-
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def _convert_point_format_to_abs_origin(point, image_ele: dict, *, src_format: str):
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x, y = point
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if src_format == "abs_origin":
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new_point = [int(x), int(y)]
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elif src_format == "abs_resized":
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new_point = [
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int(x / image_ele["resized_width"] * image_ele["width"]),
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int(y / image_ele["resized_height"] * image_ele["height"]),
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]
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elif src_format == "qwen-vl":
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new_point = [
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int(x / 999 * image_ele["width"]),
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int(y / 999 * image_ele["height"]),
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]
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elif src_format == "rel":
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new_point = [
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int(x * image_ele["width"]),
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int(y * image_ele["height"]),
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]
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elif src_format == "molmo":
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new_point = [
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int(x / 100 * image_ele["width"]),
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int(y / 100 * image_ele["height"]),
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]
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else:
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assert False, f"Unknown src_format: {src_format}"
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return new_point
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-
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def convert_point_format(point, image_ele: dict, *, src_format: str, tgt_format: str):
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point_abs_origin = _convert_point_format_to_abs_origin(point, image_ele, src_format=src_format)
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point_tgt_format = _convert_point_format_from_abs_origin(point_abs_origin, image_ele, tgt_format=tgt_format)
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return point_tgt_format
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__all__ = [
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"update_image_size_",
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"convert_bbox_format",
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"convert_point_format",
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]
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