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https://github.com/datalab-to/chandra.git
synced 2025-11-29 00:23:12 +00:00
Support different bbox format
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@@ -5,6 +5,7 @@ from transformers import Qwen3VLForConditionalGeneration, Qwen3VLProcessor
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from chandra.model.schema import BatchInputItem, GenerationResult
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from chandra.model.util import scale_to_fit
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from chandra.output import fix_raw
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from chandra.prompts import PROMPT_MAPPING
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from chandra.settings import settings
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@@ -42,7 +43,7 @@ def generate_hf(
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clean_up_tokenization_spaces=False,
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)
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results = [
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GenerationResult(raw=out, token_count=len(ids), error=False)
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GenerationResult(raw=fix_raw(out), token_count=len(ids), error=False)
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for out, ids in zip(output_text, generated_ids_trimmed)
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]
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return results
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@@ -9,6 +9,7 @@ from openai import OpenAI
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from chandra.model.schema import BatchInputItem, GenerationResult
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from chandra.model.util import scale_to_fit, detect_repeat_token
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from chandra.output import fix_raw
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from chandra.prompts import PROMPT_MAPPING
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from chandra.settings import settings
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@@ -74,8 +75,10 @@ def generate_vllm(
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temperature=temperature,
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top_p=top_p,
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)
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raw = completion.choices[0].message.content
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raw = fix_raw(raw)
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result = GenerationResult(
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raw=completion.choices[0].message.content,
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raw=raw,
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token_count=completion.usage.completion_tokens,
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error=False,
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)
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@@ -20,6 +20,15 @@ def get_image_name(html: str, div_idx: int):
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return f"{html_hash}_{div_idx}_img.webp"
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def fix_raw(html: str):
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def replace_group(match):
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numbers = re.findall(r"\d+", match.group(0))
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return "[" + ",".join(numbers) + "]"
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result = re.sub(r"(?:<BBOX\d+>){4}", replace_group, html)
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return result
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def extract_images(html: str, chunks: dict, image: Image.Image):
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images = {}
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div_idx = 0
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@@ -228,10 +237,11 @@ def parse_layout(html: str, image: Image.Image):
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layout_blocks = []
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for div in top_level_divs:
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bbox = div.get("data-bbox")
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try:
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bbox = json.loads(bbox)
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except Exception:
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bbox = [0, 0, 1, 1] # Fallback to a default bbox if parsing fails
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bbox = [0, 0, 1, 1]
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bbox = list(map(int, bbox))
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# Normalize bbox
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