import math def round_by_factor(number: int, factor: int) -> int: """返回最接近 number 的且能被 factor 整除的整数""" return round(number / factor) * factor def ceil_by_factor(number: int, factor: int) -> int: """返回大于等于 number 的且能被 factor 整除的整数""" return math.ceil(number / factor) * factor def floor_by_factor(number: int, factor: int) -> int: """返回小于等于 number 的且能被 factor 整除的整数""" return math.floor(number / factor) * factor def smart_resize(height, width, factor=28, min_pixels=56 * 56, max_pixels=14 * 14 * 4 * 1280, max_long_side=8192): """缩放后图片满足以下条件: 1. 长宽能被 factor 整除 2. pixels 总数被限制在 [min_pixels, max_pixels] 内 3. 最长边限制在 max_long_side 内 4. 保证其长宽比基本不变 """ if height < 2 or width < 2: raise ValueError(f"height:{height} or width:{width} must be larger than factor:{factor}") elif max(height, width) / min(height, width) > 200: raise ValueError(f"absolute aspect ratio must be smaller than 100, got {height} / {width}") if max(height, width) > max_long_side: beta = max(height, width) / max_long_side height, width = int(height / beta), int(width / beta) h_bar = round_by_factor(height, factor) w_bar = round_by_factor(width, factor) if h_bar * w_bar > max_pixels: beta = math.sqrt((height * width) / max_pixels) h_bar = floor_by_factor(height / beta, factor) w_bar = floor_by_factor(width / beta, factor) elif h_bar * w_bar < min_pixels: beta = math.sqrt(min_pixels / (height * width)) h_bar = ceil_by_factor(height * beta, factor) w_bar = ceil_by_factor(width * beta, factor) return h_bar, w_bar def update_image_size_(image_ele: dict, min_tokens=1, max_tokens=12800, merge_base=2, patch_size=14): """根据 min_tokens, max_tokens 更新 image_ele 的尺寸信息 Args: image_ele (dict): - image_ele["image"]: str 图片路径 - image_ele["height"]: int 图片原始高度 - image_ele["width"]: int 图片原始宽度 Returns: 更新后的 image_ele, 新增如下 key-value pair dict: - image_ele["resized_height"]: int 输入到模型的真实高度 - image_ele["resized_width"]: int 输入到模型的真实宽度 - image_ele["seq_len"]: int 输入到模型所占的序列长度 """ height, width = image_ele["height"], image_ele["width"] pixels_per_token = patch_size * patch_size * merge_base * merge_base resized_height, resized_width = smart_resize( height, width, factor=merge_base * patch_size, min_pixels=pixels_per_token * min_tokens, max_pixels=pixels_per_token * max_tokens, max_long_side=50000, ) image_ele.update( { "resized_height": resized_height, "resized_width": resized_width, "seq_len": resized_height * resized_width // pixels_per_token + 2, } ) return image_ele def _convert_bbox_format_from_abs_origin(bbox, image_ele: dict, *, tgt_format: str): x1, y1, x2, y2 = bbox if tgt_format == "abs_origin": new_bbox = [int(x1), int(y1), int(x2), int(y2)] elif tgt_format == "abs_resized": new_bbox = [ int(x1 / image_ele["width"] * image_ele["resized_width"]), int(y1 / image_ele["height"] * image_ele["resized_height"]), int(x2 / image_ele["width"] * image_ele["resized_width"]), int(y2 / image_ele["height"] * image_ele["resized_height"]), ] elif tgt_format == "qwen-vl": new_bbox = [ int(x1 / image_ele["width"] * 999), int(y1 / image_ele["height"] * 999), int(x2 / image_ele["width"] * 999), int(y2 / image_ele["height"] * 999), ] elif tgt_format == "rel": new_bbox = [ float(x1 / image_ele["width"]), float(y1 / image_ele["height"]), float(x2 / image_ele["width"]), float(y2 / image_ele["height"]), ] elif tgt_format == "molmo": new_bbox = [ round(x1 / image_ele["width"] * 100, ndigits=1), round(y1 / image_ele["height"] * 100, ndigits=1), round(x2 / image_ele["width"] * 100, ndigits=1), round(y2 / image_ele["height"] * 100, ndigits=1), ] else: assert False, f"Unknown tgt_format: {tgt_format}" return new_bbox def _convert_bbox_format_to_abs_origin(bbox, image_ele: dict, *, src_format: str): x1, y1, x2, y2 = bbox if src_format == "abs_origin": new_bbox = [int(x1), int(y1), int(x2), int(y2)] elif src_format == "abs_resized": new_bbox = [ int(x1 / image_ele["resized_width"] * image_ele["width"]), int(y1 / image_ele["resized_height"] * image_ele["height"]), int(x2 / image_ele["resized_width"] * image_ele["width"]), int(y2 / image_ele["resized_height"] * image_ele["height"]), ] elif src_format == "qwen-vl": new_bbox = [ int(x1 / 999 * image_ele["width"]), int(y1 / 999 * image_ele["height"]), int(x2 / 999 * image_ele["width"]), int(y2 / 999 * image_ele["height"]), ] elif src_format == "rel": new_bbox = [ int(x1 * image_ele["width"]), int(y1 * image_ele["height"]), int(x2 * image_ele["width"]), int(y2 * image_ele["height"]), ] elif src_format == "molmo": new_bbox = [ int(x1 / 100 * image_ele["width"]), int(y1 / 100 * image_ele["height"]), int(x2 / 100 * image_ele["width"]), int(y2 / 100 * image_ele["height"]), ] else: assert False, f"Unknown src_format: {src_format}" return new_bbox def convert_bbox_format(bbox, image_ele: dict, *, src_format: str, tgt_format: str): bbox_abs_origin = _convert_bbox_format_to_abs_origin(bbox, image_ele, src_format=src_format) bbox_tgt_format = _convert_bbox_format_from_abs_origin(bbox_abs_origin, image_ele, tgt_format=tgt_format) return bbox_tgt_format def _convert_point_format_from_abs_origin(point, image_ele: dict, *, tgt_format: str): x, y = point if tgt_format == "abs_origin": new_point = [int(x), int(y)] elif tgt_format == "abs_resized": new_point = [ int(x / image_ele["width"] * image_ele["resized_width"]), int(y / image_ele["height"] * image_ele["resized_height"]), ] elif tgt_format == "qwen-vl": new_point = [ int(x / image_ele["width"] * 999), int(y / image_ele["height"] * 999), ] elif tgt_format == "rel": new_point = [ float(x / image_ele["width"]), float(y / image_ele["height"]), ] elif tgt_format == "molmo": new_point = [ round(x / image_ele["width"] * 100, ndigits=1), round(y / image_ele["height"] * 100, ndigits=1), ] else: assert False, f"Unknown tgt_format: {tgt_format}" return new_point def _convert_point_format_to_abs_origin(point, image_ele: dict, *, src_format: str): x, y = point if src_format == "abs_origin": new_point = [int(x), int(y)] elif src_format == "abs_resized": new_point = [ int(x / image_ele["resized_width"] * image_ele["width"]), int(y / image_ele["resized_height"] * image_ele["height"]), ] elif src_format == "qwen-vl": new_point = [ int(x / 999 * image_ele["width"]), int(y / 999 * image_ele["height"]), ] elif src_format == "rel": new_point = [ int(x * image_ele["width"]), int(y * image_ele["height"]), ] elif src_format == "molmo": new_point = [ int(x / 100 * image_ele["width"]), int(y / 100 * image_ele["height"]), ] else: assert False, f"Unknown src_format: {src_format}" return new_point def convert_point_format(point, image_ele: dict, *, src_format: str, tgt_format: str): point_abs_origin = _convert_point_format_to_abs_origin(point, image_ele, src_format=src_format) point_tgt_format = _convert_point_format_from_abs_origin(point_abs_origin, image_ele, tgt_format=tgt_format) return point_tgt_format __all__ = [ "update_image_size_", "convert_bbox_format", "convert_point_format", ] if __name__ == "__main__": from PIL import Image def draw_point(image: Image.Image, point: list): from copy import deepcopy from PIL import ImageDraw image = deepcopy(image) image_draw = ImageDraw.Draw(image) image_draw.ellipse([point[0] - 5, point[1] - 5, point[0] + 5, point[1] + 5], fill="red") return image # image_ele = { # "image": "http://ofasys-multimodal-wlcb-3.oss-cn-wulanchabu.aliyuncs.com/data/datacomp1b/image/19774238/7218d7ceb39e82e0cafc389f326e218da623a8f2.jpg", # "height": 444, # "width": 592, # } image_ele = { "image": "46d5402b2c183f996f2a13cd2016af15.png", "height": 1080, "width": 1920, } point = [0.8379917184, 0.2087912088] # rel, keyboard 'k' in the image # image: Image.Image = Image.open(requests.get(image_ele["image"], stream=True).raw) image: Image.Image = Image.open(image_ele["image"]) assert image.width == image_ele["width"] and image.height == image_ele["height"], f"{image.size=}, {image_ele=}" resized_image = image.resize((image_ele["resized_width"], image_ele["resized_height"])) draw_point(image, [point[0] * image.width, point[1] * image.height]).save("image_1.png") image_ele = update_image_size_(image_ele) point = convert_point_format(point, image_ele, src_format="rel", tgt_format="abs_resized") print(f"{image_ele=}\n{point=}") draw_point(resized_image, point).save("image_2.png")