From e6e2d7da22d6cbf6c666d29dde9b6cdc4854cea5 Mon Sep 17 00:00:00 2001 From: Vik Paruchuri Date: Thu, 30 Jan 2025 10:48:39 -0500 Subject: [PATCH] Clean up benchmarks --- README.md | 4 +- benchmarks/overall/inference.py | 78 +++--- benchmarks/overall/overall.py | 107 +++++--- benchmarks/overall/schema.py | 15 + benchmarks/overall/scoring.py | 143 ++++++++-- benchmarks/table/table.py | 1 + marker/processors/llm/llm_complex.py | 2 +- marker/processors/llm/llm_handwriting.py | 2 +- marker/renderers/markdown.py | 14 +- poetry.lock | 332 +++++++++++------------ pyproject.toml | 3 +- 11 files changed, 410 insertions(+), 291 deletions(-) create mode 100644 benchmarks/overall/schema.py diff --git a/README.md b/README.md index 0a3382a8..be37250f 100644 --- a/README.md +++ b/README.md @@ -219,11 +219,11 @@ rendered = converter("FILEPATH") text, _, images = text_from_rendered(rendered) ``` -This takes all the same configuration as the PdfConverter. You can specify the configuration `--force_layout_block=Table` to avoid layout detection and instead assume every page is a table. +This takes all the same configuration as the PdfConverter. You can specify the configuration `force_layout_block=Table` to avoid layout detection and instead assume every page is a table. Set `output_format=json` to also get cell bounding boxes. You can also run this via the CLI with ```shell -python convert_single.py FILENAME --use_llm --force_layout_block Table --converter_cls marker.converters.table.TableConverter +marker_single FILENAME --use_llm --force_layout_block Table --converter_cls marker.converters.table.TableConverter --output_format json ``` # Output Formats diff --git a/benchmarks/overall/inference.py b/benchmarks/overall/inference.py index 040a53af..f312429b 100644 --- a/benchmarks/overall/inference.py +++ b/benchmarks/overall/inference.py @@ -1,47 +1,47 @@ -import io - -import fitz as pymupdf +import json import tempfile from bs4 import BeautifulSoup +from benchmarks.overall.scoring import score_blocks +from benchmarks.overall.schema import BlockScores from marker.converters.pdf import PdfConverter -def open_pymupdf(pdf_bytes): - stream = io.BytesIO(pdf_bytes) - return pymupdf.open(stream=stream) +def get_marker_html(marker_models: dict, pdf_bytes: bytes): + block_converter = PdfConverter( + artifact_dict=marker_models, + config={"page_range": [0], "disable_tqdm": True}, + renderer="marker.renderers.html.HTMLRenderer" + ) + with tempfile.NamedTemporaryFile(suffix=".pdf", mode="wb") as f: + f.write(pdf_bytes) + rendered = block_converter(f.name) + html = rendered.html + soup = BeautifulSoup(html, "html.parser") + inner_html = str(soup.find("body").decode_contents()) + return inner_html + + +def marker_html_func(model_dict, sample, **kwargs) -> BlockScores: + gt_blocks = json.loads(sample["gt_blocks"]) + pdf_bytes = sample["pdf"] # This is a single page PDF + marker_html = get_marker_html(model_dict, pdf_bytes) + gt_html = [block["html"] for block in gt_blocks] + scores = score_blocks(gt_html, marker_html) + return scores -def clip_pdf_to_bbox(doc, bbox, padding=1): - page = doc[0] - height, width = page.bound().height, page.bound().width - remove_left = [0, 0, bbox[0] - padding, height] - remove_top = [0, 0, width, bbox[1] - padding] - remove_right = [bbox[2] + padding, 0, width, height] - remove_bottom = [0, bbox[3] + padding, width, height] - for remove in [remove_left, remove_top, remove_right, remove_bottom]: - clip_rect = pymupdf.Rect(*remove) - page.add_redact_annot(clip_rect) - page.apply_redactions() - clip_rect = pymupdf.Rect(*bbox) - page.set_cropbox(clip_rect) - return doc +def mathpix_html_func(model_dict, sample, mathpix_ds, **kwargs) -> BlockScores: + uuid = sample["uuid"] + data = None + for row in mathpix_ds: + if str(row["uuid"]) == str(uuid): + data = row + break + if not data: + raise ValueError(f"Could not find data for uuid {uuid}") -def get_marker_block_html(marker_models: dict, gt_blocks: list, pdf_bytes: bytes): - block_html = [] - for block in gt_blocks: - bbox = block["bbox"] - doc2 = open_pymupdf(pdf_bytes) - clip_pdf_to_bbox(doc2, bbox) - block_converter = PdfConverter( - artifact_dict=marker_models, - config={"page_range": [0], "force_layout_block": block["block_type"], "disable_tqdm": True}, - renderer="marker.renderers.html.HTMLRenderer" - ) - with tempfile.NamedTemporaryFile(suffix=".pdf", mode="wb") as f: - doc2.save(f) - rendered = block_converter(f.name) - html = rendered.html - soup = BeautifulSoup(html, "html.parser") - inner_html = str(soup.find("body").decode_contents()) - block_html.append(inner_html) - return block_html \ No newline at end of file + mathpix_md = data["md"] + gt_blocks = json.loads(sample["gt_blocks"]) + gt_html = [block["html"] for block in gt_blocks] + scores = score_blocks(gt_html, mathpix_md, convert=False) + return scores diff --git a/benchmarks/overall/overall.py b/benchmarks/overall/overall.py index 57e80286..bdb1fc7c 100644 --- a/benchmarks/overall/overall.py +++ b/benchmarks/overall/overall.py @@ -1,5 +1,6 @@ import json import os +import traceback from collections import defaultdict from pathlib import Path @@ -8,64 +9,53 @@ import tabulate from tqdm import tqdm +from benchmarks.overall.inference import marker_html_func, mathpix_html_func +from benchmarks.overall.schema import FullResult from marker.logger import configure_logging from marker.models import create_model_dict -from inference import get_marker_block_html from marker.settings import settings -from scoring import score_blocks configure_logging() -@click.command(help="Benchmark PDF to MD conversion.") -@click.option("--dataset", type=str, help="Path to the benchmark dataset", default="datalab-to/marker_benchmark") -@click.option("--other_methods", type=str, help="Comma separated list of other methods to compare against. Possible values:", default="") -@click.option("--result_path", type=str, default=os.path.join(settings.OUTPUT_DIR, "benchmark", "overall"), help="Output path for results.") -@click.option("--max_rows", type=int, default=None, help="Maximum number of rows to process.") -def main( - dataset: str, - other_methods: str, - result_path: str, - max_rows: int -): - allowed_methods = [""] - methods = other_methods.split(",") - for method in methods: - if method not in allowed_methods: - raise ValueError(f"Method {method} not allowed. Allowed methods are {allowed_methods}") - - model_dict = create_model_dict() - ds = datasets.load_dataset(dataset, split="train") +def get_method_scores(ds, model_dict, max_rows=None, html_func=marker_html_func, **kwargs) -> FullResult: bench_scores = {} averages_by_type = defaultdict(list) averages_by_block_type = defaultdict(list) for idx, sample in tqdm(enumerate(ds), desc="Running benchmark"): + if max_rows is not None and idx >= max_rows: + break + gt_blocks = json.loads(sample["gt_blocks"]) doc_type = sample["classification"] - pdf_bytes = sample["pdf"] # This is a single page PDF - marker_html = get_marker_block_html(model_dict, gt_blocks, pdf_bytes) - gt_html = [block["html"] for block in gt_blocks] - scores = score_blocks(gt_html, marker_html) - gt_weights = [len(ht) for ht in gt_html] - overall_score = sum([s * w for s, w in zip(scores, gt_weights)]) / sum(gt_weights) - bench_scores[idx] = { - "scores": scores, - "weights": gt_weights, - "overall_score": overall_score # Weighted score, weighted by length of GT block - } - - averages_by_type[doc_type].append(overall_score) - - for score, gt_block in zip(scores, gt_blocks): + try: + scores = html_func(model_dict, sample, **kwargs) + except ValueError as e: + print(f"Error with sample {idx}: {e}") + continue + averages_by_type[doc_type].append(scores["overall_score"]) + + for score, gt_block in zip(scores["scores"], gt_blocks): averages_by_block_type[gt_block["block_type"]].append(score) - if max_rows is not None and idx >= max_rows: - break + bench_scores[idx] = scores + + return { + "raw_scores": bench_scores, + "averages_by_type": averages_by_type, + "averages_by_block_type": averages_by_block_type + } + +def print_scores(scores: FullResult, method: str): + averages_by_type = scores["averages_by_type"] + averages_by_block_type = scores["averages_by_block_type"] + bench_scores = scores["raw_scores"] for k in averages_by_type: averages_by_type[k] = sum(averages_by_type[k]) / len(averages_by_type[k]) averages_by_type = sorted(averages_by_type.items()) + print(f"Scores for method {method}:") print(tabulate.tabulate(averages_by_type, headers=["Document Type", "Average Score"], tablefmt="github")) for k in averages_by_block_type: @@ -76,10 +66,45 @@ def main( overall_average = sum([bench_scores[k]["overall_score"] for k in bench_scores]) / len(bench_scores) print(tabulate.tabulate([["Overall Average", overall_average]], tablefmt="github")) + print() + +@click.command(help="Benchmark PDF to MD conversion.") +@click.option("--dataset", type=str, help="Path to the benchmark dataset", default="datalab-to/marker_benchmark") +@click.option("--other_methods", type=str, help="Comma separated list of other methods to compare against. Possible values: mathpix", default="") +@click.option("--result_path", type=str, default=os.path.join(settings.OUTPUT_DIR, "benchmark", "overall"), help="Output path for results.") +@click.option("--max_rows", type=int, default=None, help="Maximum number of rows to process.") +def main( + dataset: str, + other_methods: str, + result_path: str, + max_rows: int +): + allowed_methods = ["mathpix", ""] + methods = other_methods.split(",") + for method in methods: + if method not in allowed_methods: + raise ValueError(f"Method {method} not allowed. Allowed methods are {allowed_methods}") + + model_dict = create_model_dict() + ds = datasets.load_dataset(dataset, split="train") + + marker_scores = get_method_scores(ds, model_dict, max_rows=max_rows) + all_scores = { + "marker": marker_scores + } + + if "mathpix" in methods: + mathpix_ds = datasets.load_dataset("datalab-to/marker_benchmark_mathpix", split="train") + mathpix_scores = get_method_scores(ds, model_dict, max_rows=max_rows, html_func=mathpix_html_func, mathpix_ds=mathpix_ds) + all_scores["mathpix"] = mathpix_scores + + for k,v in all_scores.items(): + print_scores(v, k) - out_path = Path(result_path) / "overall.json" - with open(out_path, "w") as f: - json.dump(bench_scores, f, indent=2) + out_path = Path(result_path) + out_path.mkdir(parents=True, exist_ok=True) + with open(out_path / "overall.json", "w") as f: + json.dump(all_scores, f, indent=2) print(f"Results saved to {out_path}.") diff --git a/benchmarks/overall/schema.py b/benchmarks/overall/schema.py new file mode 100644 index 00000000..98ffc1b8 --- /dev/null +++ b/benchmarks/overall/schema.py @@ -0,0 +1,15 @@ +from typing import TypedDict, List, Dict + + +class BlockScores(TypedDict): + scores: List[float] + order_score: float + gt: List[str] + method: str + overall_score: float + + +class FullResult(TypedDict): + raw_scores: Dict[int, BlockScores] + averages_by_type: Dict[str, List[float]] + averages_by_block_type: Dict[str, List[float]] diff --git a/benchmarks/overall/scoring.py b/benchmarks/overall/scoring.py index 3ae19a98..1ba78bc9 100644 --- a/benchmarks/overall/scoring.py +++ b/benchmarks/overall/scoring.py @@ -1,30 +1,135 @@ -import re -from bs4 import BeautifulSoup +from typing import List -from markdownify import markdownify as md from rapidfuzz import fuzz -def standardize_html(html): - soup = BeautifulSoup(html, "html.parser") +from benchmarks.overall.schema import BlockScores +from marker.renderers.markdown import MarkdownRenderer +import re + + +def kendall_tau(correct_order: List[int], actual_order: List[int]) -> float: + n = len(correct_order) + concordant = 0 + discordant = 0 + + for i in range(n): + for j in range(i + 1, n): + correct_sign = correct_order[i] - correct_order[j] + actual_sign = actual_order[i] - actual_order[j] + + if (correct_sign > 0 and actual_sign > 0) or (correct_sign < 0 and actual_sign < 0): + concordant += 1 + elif (correct_sign < 0 and actual_sign > 0) or (correct_sign > 0 and actual_sign < 0): + discordant += 1 + + total_pairs = (n * (n - 1)) // 2 + tau = (concordant - discordant) / total_pairs + tau = (tau + 1) / 2 # 0-1 scale + return tau * 100 # 0-100 scale + + +def find_fuzzy_alignments( + main_string: str, + substrings: List[str], + threshold: int = 70 +) -> List[dict]: + alignments = [] + + for idx, substr in enumerate(substrings): + result = fuzz.partial_ratio_alignment(substr, main_string, score_cutoff=threshold) + + score = 0 + dest_start = 0 + dest_end = 0 + if result: + score = result.score + dest_start = result.dest_start + dest_end = result.dest_end + + alignments.append({ + "string": substr, + "start": dest_start, + "end": dest_end, + "score": score, + "idx": idx + }) + return alignments - # Convert all headers to h1 so we don't penalize small differences in header levels - for tag in soup.find_all(["h1", "h2", "h3", "h4", "h5", "h6"]): - tag.name = "h1" +def convert_to_md(html): + md = MarkdownRenderer() + markdown = md.md_cls.convert(html) + return markdown + +def standardize_markdown(markdown): + pattern = r'(?", "\n") + markdown = re.sub(r"(.*?)", r"\1", markdown) + markdown = re.sub(r"(.*?)", r"\1", markdown) + markdown = re.sub(r"\s+", " ", markdown) markdown = re.sub(r"\n+", "\n", markdown) markdown = re.sub("\\.+", ".", markdown) # Replace repeated periods with a single period, like in table of contents - return markdown.strip() + markdown = re.sub("#+", "#", markdown) # Replace repeated headers with a single header + markdown = re.sub(r"\$", "", markdown) # Remove equation delimiters + return markdown.strip().lower() + + +def standardize_math(match): + try: + delim = "$$" if match.group(0).startswith('$$') else "$" + math_content = match.group(1) or match.group(2) + result = clean_latex(math_content) + return f'{delim}{result}{delim}' + except Exception as e: + print(f"Failed to standardize math expression: {match.group(0)} with error: {e}") + return match.group(0) + + +def clean_latex(latex_str): + latex_str = re.sub(r'\s+', ' ', latex_str.strip()) + for tag in [r'\\text', r'\\mathrm', r'\\mathbf', r'\\textbf']: + latex_str = re.sub(tag + r'\{([^}]+)\}', r'\1', latex_str) + + + replacements = { + '\\times': '*', + '\\cdot': '*', + '\\div': '/', + '\\le': '<=', + '\\ge': '>=', + '\\neq': '!=', + '\\to': '\\rightarrow', + } + + for old, new in replacements.items(): + latex_str = latex_str.replace(old, new) + + return latex_str + +def score_blocks(gt_html, method_html, convert=True) -> BlockScores: + if convert: + method_html = convert_to_md(method_html) + method_html = standardize_markdown(method_html) + gt = [standardize_markdown(convert_to_md(gt)) for gt in gt_html] + alignments = find_fuzzy_alignments(method_html, gt) + scores = [alignment["score"] for alignment in alignments] + orders = [alignment["start"] for alignment in alignments] + correct_order = range(len(gt)) + actual_order = sorted(range(len(gt)), key=lambda x: orders[x]) + order_score = kendall_tau(correct_order, actual_order) + gt_weights = [len(g) for g in gt] + weighted_scores = [score * weight for score, weight in zip(scores, gt_weights)] -def score_blocks(gt_html, method_html): - scores = [] - for gt, method in zip(gt_html, method_html): - gt= standardize_html(gt) - method = standardize_html(method) - score = fuzz.ratio(gt, method) - scores.append(score) - return scores \ No newline at end of file + # Weight the score by sequence length + overall_score = sum(weighted_scores) / max(1, sum(gt_weights)) + overall_score = overall_score * 0.8 + order_score * 0.2 + return { + "scores": scores, + "order_score": order_score, + "gt": gt, + "method": method_html, + "overall_score": overall_score + } \ No newline at end of file diff --git a/benchmarks/table/table.py b/benchmarks/table/table.py index dfeb5eb0..448e32fe 100644 --- a/benchmarks/table/table.py +++ b/benchmarks/table/table.py @@ -223,6 +223,7 @@ def main( } out_path = Path(result_path) / "table.json" + out_path.mkdir(parents=True, exist_ok=True) with open(out_path, "w+") as f: json.dump(results, f, indent=2) diff --git a/marker/processors/llm/llm_complex.py b/marker/processors/llm/llm_complex.py index 52c46364..6d58a077 100644 --- a/marker/processors/llm/llm_complex.py +++ b/marker/processors/llm/llm_complex.py @@ -85,4 +85,4 @@ def process_rewriting(self, document: Document, page: PageGroup, block: Block): # Convert LLM markdown to html corrected_markdown = corrected_markdown.strip().lstrip("```markdown").rstrip("```").strip() - block.html = markdown2.markdown(corrected_markdown) \ No newline at end of file + block.html = markdown2.markdown(corrected_markdown, extras=["tables"]) \ No newline at end of file diff --git a/marker/processors/llm/llm_handwriting.py b/marker/processors/llm/llm_handwriting.py index d3e9b9f3..10a0c25b 100644 --- a/marker/processors/llm/llm_handwriting.py +++ b/marker/processors/llm/llm_handwriting.py @@ -72,4 +72,4 @@ def process_rewriting(self, document: Document, page: PageGroup, block: Handwrit return markdown = markdown.strip().lstrip("```markdown").rstrip("```").strip() - block.html = markdown2.markdown(markdown) + block.html = markdown2.markdown(markdown, extras=["tables"]) diff --git a/marker/renderers/markdown.py b/marker/renderers/markdown.py index 9a48fa40..722470c1 100644 --- a/marker/renderers/markdown.py +++ b/marker/renderers/markdown.py @@ -198,10 +198,9 @@ class MarkdownRenderer(HTMLRenderer): inline_math_delimiters: Annotated[Tuple[str], "The delimiters to use for inline math."] = ("$", "$") block_math_delimiters: Annotated[Tuple[str], "The delimiters to use for block math."] = ("$$", "$$") - def __call__(self, document: Document) -> MarkdownOutput: - document_output = document.render() - full_html, images = self.extract_html(document, document_output) - md_cls = Markdownify( + @property + def md_cls(self): + return Markdownify( self.paginate_output, self.page_separator, heading_style="ATX", @@ -215,7 +214,12 @@ def __call__(self, document: Document) -> MarkdownOutput: inline_math_delimiters=self.inline_math_delimiters, block_math_delimiters=self.block_math_delimiters ) - markdown = md_cls.convert(full_html) + + + def __call__(self, document: Document) -> MarkdownOutput: + document_output = document.render() + full_html, images = self.extract_html(document, document_output) + markdown = self.md_cls.convert(full_html) markdown = cleanup_text(markdown) return MarkdownOutput( markdown=markdown, diff --git a/poetry.lock b/poetry.lock index c053780c..471d43c1 100644 --- a/poetry.lock +++ b/poetry.lock @@ -801,13 +801,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "fastapi" -version = "0.115.7" +version = "0.115.8" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" optional = false python-versions = ">=3.8" files = [ - {file = "fastapi-0.115.7-py3-none-any.whl", hash = "sha256:eb6a8c8bf7f26009e8147111ff15b5177a0e19bb4a45bc3486ab14804539d21e"}, - {file = "fastapi-0.115.7.tar.gz", hash = "sha256:0f106da6c01d88a6786b3248fb4d7a940d071f6f488488898ad5d354b25ed015"}, + {file = "fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf"}, + {file = "fastapi-0.115.8.tar.gz", hash = "sha256:0ce9111231720190473e222cdf0f07f7206ad7e53ea02beb1d2dc36e2f0741e9"}, ] [package.dependencies] @@ -1367,13 +1367,13 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "huggingface-hub" -version = "0.28.0" +version = "0.28.1" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" files = [ - {file = "huggingface_hub-0.28.0-py3-none-any.whl", hash = "sha256:71cff4e500efe68061d94b7f6d3114e183715088be7a90bf4dd84af83b5f5cdb"}, - {file = "huggingface_hub-0.28.0.tar.gz", hash = "sha256:c2b18c02a47d4384763caddb4d0ab2a8fc6c16e0800d6de4d55d0a896244aba3"}, + {file = "huggingface_hub-0.28.1-py3-none-any.whl", hash = "sha256:aa6b9a3ffdae939b72c464dbb0d7f99f56e649b55c3d52406f49e0a5a620c0a7"}, + {file = "huggingface_hub-0.28.1.tar.gz", hash = "sha256:893471090c98e3b6efbdfdacafe4052b20b84d59866fb6f54c33d9af18c303ae"}, ] [package.dependencies] @@ -1826,13 +1826,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (> [[package]] name = "jupyterlab" -version = "4.3.4" +version = "4.3.5" description = "JupyterLab computational environment" optional = false python-versions = ">=3.8" files = [ - {file = 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