a4f8fe2f00
* update for autoglm-v * Update run_autoglm.py --------- Co-authored-by: hanyullai <hanyullai@outlook.com>
101 lines
3.8 KiB
Python
101 lines
3.8 KiB
Python
import re
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def parse_line(line):
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# 解析格式，如：label Google Chrome (191, 13) (104, 17)
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pattern = r"^(\S+)\s+(.+?)\s+\((\d+), (\d+)\)\s+\((\d+), (\d+)\)"
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m = re.match(pattern, line)
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if not m:
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return None
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node_type, text, cx, cy, w, h = m.groups()
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cx, cy, w, h = map(int, (cx, cy, w, h))
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# bounding box as (x1, y1, x2, y2)
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x1 = cx - w // 2
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y1 = cy - h // 2
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x2 = x1 + w
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y2 = y1 + h
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return {
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"type": node_type,
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"text": text.strip(),
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"bbox": (x1, y1, x2, y2),
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"center": (cx, cy),
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"size": (w, h),
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"raw": line,
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}
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def iou(box1, box2):
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# box: (x1, y1, x2, y2)
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xi1 = max(box1[0], box2[0])
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yi1 = max(box1[1], box2[1])
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xi2 = min(box1[2], box2[2])
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yi2 = min(box1[3], box2[3])
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inter_width = max(0, xi2 - xi1)
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inter_height = max(0, yi2 - yi1)
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inter_area = inter_width * inter_height
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area1 = (box1[2] - box1[0]) * (box1[3] - box1[1])
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area2 = (box2[2] - box2[0]) * (box2[3] - box2[1])
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union = area1 + area2 - inter_area
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if union == 0:
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return 0
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return inter_area / union
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def norm_text(s):
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# 归一化文本：小写、去空格等
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return re.sub(r"\s+", "", s.lower())
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def text_similarity(a, b):
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# 简单判定：完全一致为1，否则0
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na, nb = norm_text(a), norm_text(b)
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if na == nb:
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return 1.0
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else:
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return 0
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def filter_similar_nodes(linearized_accessibility_tree):
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lines = [ln for ln in linearized_accessibility_tree.split("\n") if ln.strip()]
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# parse all nodes
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nodes = []
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for ln in lines:
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node = parse_line(ln)
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if node:
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nodes.append(node)
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else:
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# 解析不了的保留
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nodes.append({"raw": ln, "invalid": True})
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filtered = []
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removed = [False] * len(nodes)
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# 阈值可自行调整
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IOU_THRESH = 0.2
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TEXT_THRESH = 0.9
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for i, ni in enumerate(nodes):
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if ni.get("invalid"):
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filtered.append(ni["raw"])
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continue
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if removed[i]:
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continue
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for j in range(i + 1, len(nodes)):
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nj = nodes[j]
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if nj.get("invalid"):
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continue
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iou_val = iou(ni["bbox"], nj["bbox"])
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text_sim = text_similarity(ni["text"], nj["text"])
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if iou_val > IOU_THRESH and text_sim > TEXT_THRESH:
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# 二者极其相似，移除后者
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removed[j] = True
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# print(f"移除: {nj['raw']} (与 {ni['raw']} 相似度高)")
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# 保留未被标记为移除的
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if not removed[i]:
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filtered.append(ni["raw"])
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return "\n".join(filtered)
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# 示例用法
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if __name__ == "__main__":
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linearized_accessibility_tree = "tag\ttext\tposition (center x & y)\tsize (w & h)\nicon\t\t(1853, 1001)\t(64, 64)\nlabel\tHome\t(1853, 1045)\t(40, 17)\nlabel\tActivities\t(49, 13)\t(63, 17)\ntext\tActivities\t(49, 13)\t(63, 17)\nlabel\tApr 17 17∶04\t(995, 13)\t(117, 27)\ntext\tApr 17 17∶04\t(995, 13)\t(87, 18)\nmenu\tSystem\t(1867, 13)\t(106, 27)\npush-button\tGoogle Chrome\t(35, 65)\t(70, 64)\npush-button\tThunderbird Mail\t(35, 133)\t(70, 64)\npush-button\tVisual Studio Code\t(35, 201)\t(70, 64)\npush-button\tVLC media player\t(35, 269)\t(70, 64)\npush-button\tLibreOffice Writer\t(35, 337)\t(70, 64)\npush-button\tLibreOffice Calc\t(35, 405)\t(70, 64)\npush-button\tLibreOffice Impress\t(35, 473)\t(70, 64)\npush-button\tGNU Image Manipulation Program\t(35, 541)\t(70, 64)\npush-button\tFiles\t(35, 609)\t(70, 64)\npush-button\tUbuntu Software\t(35, 677)\t(70, 64)\npush-button\tHelp\t(35, 745)\t(70, 64)\npush-button\tTrash\t(35, 816)\t(70, 64)\ntoggle-button\tShow Applications\t(35, 1045)\t(70, 70)"
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result = filter_similar_nodes(linearized_accessibility_tree)
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print(result)
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