Merge pull request #2622 from myhloli/dev

Dev

mineru/backend/vlm/vlm_analyze.py

@@ -9,6 +9,7 @@ from .base_predictor import BasePredictor
 from .predictor import get_predictor
 from .token_to_middle_json import result_to_middle_json
 from ...utils.enum_class import ModelPath
+from ...utils.models_download_utils import auto_download_and_get_model_root_path
 
 
 class ModelSingleton:
@@ -28,6 +29,8 @@ class ModelSingleton:
     ) -> BasePredictor:
         key = (backend,)
         if key not in self._models:
+            if not model_path:
+                model_path = auto_download_and_get_model_root_path("/","vlm")
             self._models[key] = get_predictor(
                 backend=backend,
                 model_path=model_path,
@@ -40,8 +43,8 @@ def doc_analyze(
     pdf_bytes,
     image_writer: DataWriter | None,
     predictor: BasePredictor | None = None,
-    backend="huggingface",
-    model_path=ModelPath.vlm_root_hf,
+    backend="transformers",
+    model_path: str | None = None,
     server_url: str | None = None,
 ):
     if predictor is None:
@@ -53,10 +56,10 @@ def doc_analyze(
     # load_images_time = round(time.time() - load_images_start, 2)
     # logger.info(f"load images cost: {load_images_time}, speed: {round(len(images_base64_list)/load_images_time, 3)} images/s")
 
-    infer_start = time.time()
+    # infer_start = time.time()
     results = predictor.batch_predict(images=images_base64_list)
-    infer_time = round(time.time() - infer_start, 2)
-    logger.info(f"infer finished, cost: {infer_time}, speed: {round(len(results)/infer_time, 3)} page/s")
+    # infer_time = round(time.time() - infer_start, 2)
+    # logger.info(f"infer finished, cost: {infer_time}, speed: {round(len(results)/infer_time, 3)} page/s")
 
     middle_json = result_to_middle_json(results, images_list, pdf_doc, image_writer)
     return middle_json, results
@@ -66,8 +69,8 @@ async def aio_doc_analyze(
     pdf_bytes,
     image_writer: DataWriter | None,
     predictor: BasePredictor | None = None,
-    backend="huggingface",
-    model_path=ModelPath.vlm_root_hf,
+    backend="transformers",
+    model_path: str | None = None,
     server_url: str | None = None,
 ):
     if predictor is None:

mineru/cli/client.py

@@ -41,17 +41,18 @@ from .common import do_parse, read_fn, pdf_suffixes, image_suffixes
     auto: Automatically determine the method based on the file type.
     txt: Use text extraction method.
     ocr: Use OCR method for image-based PDFs.
-    Without method specified, 'auto' will be used by default.""",
+    Without method specified, 'auto' will be used by default.
+    Adapted only for the case where the backend is set to "pipeline".""",
     default='auto',
 )
 @click.option(
     '-b',
     '--backend',
     'backend',
-    type=click.Choice(['pipeline', 'vlm-huggingface', 'vlm-sglang-engine', 'vlm-sglang-client']),
+    type=click.Choice(['pipeline', 'vlm-transformers', 'vlm-sglang-engine', 'vlm-sglang-client']),
     help="""the backend for parsing pdf:
     pipeline: More general.
-    vlm-huggingface: More general.
+    vlm-transformers: More general.
     vlm-sglang-engine: Faster(engine).
     vlm-sglang-client: Faster(client).
     without method specified, pipeline will be used by default.""",

mineru/cli/common.py

@@ -16,7 +16,6 @@ from mineru.backend.pipeline.pipeline_analyze import doc_analyze as pipeline_doc
 from mineru.data.data_reader_writer import FileBasedDataWriter
 from mineru.utils.draw_bbox import draw_layout_bbox, draw_span_bbox
 from mineru.utils.enum_class import MakeMode
-from mineru.utils.models_download_utils import auto_download_and_get_model_root_path
 from mineru.utils.pdf_image_tools import images_bytes_to_pdf_bytes
 
 pdf_suffixes = [".pdf"]
@@ -173,8 +172,7 @@ def do_parse(
             pdf_bytes = convert_pdf_bytes_to_bytes_by_pypdfium2(pdf_bytes, start_page_id, end_page_id)
             local_image_dir, local_md_dir = prepare_env(output_dir, pdf_file_name, parse_method)
             image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(local_md_dir)
-            model_path = auto_download_and_get_model_root_path('/', 'vlm')
-            middle_json, infer_result = vlm_doc_analyze(pdf_bytes, image_writer=image_writer, backend=backend, model_path=model_path, server_url=server_url)
+            middle_json, infer_result = vlm_doc_analyze(pdf_bytes, image_writer=image_writer, backend=backend, server_url=server_url)
 
             pdf_info = middle_json["pdf_info"]
 

mineru/model/vlm_sglang_model/model.py

@@ -22,6 +22,7 @@ from transformers import (
 
 from ..vlm_hf_model.configuration_mineru2 import Mineru2QwenConfig
 from ..vlm_hf_model.modeling_mineru2 import build_vision_projector
+from ...utils.models_download_utils import auto_download_and_get_model_root_path
 
 
 def flatten_nested_list(nested_list):
@@ -61,6 +62,9 @@ class Mineru2QwenForCausalLM(nn.Module):
 
         # load vision tower
         mm_vision_tower = self.config.mm_vision_tower
+        model_root_path = auto_download_and_get_model_root_path("/", "vlm")
+        mm_vision_tower = f"{model_root_path}/{mm_vision_tower}"
+
         if "clip" in mm_vision_tower:
             vision_config = CLIPVisionConfig.from_pretrained(mm_vision_tower)
             self.vision_tower = CLIPVisionModel(vision_config)  # type: ignore

mineru/model/vlm_sglang_model/server.py

@@ -27,16 +27,27 @@ async def custom_generate_request(obj: GenerateReqInput, request: Request):
 
 
 def main():
-    server_args = prepare_server_args(sys.argv[1:])
+    # 检查命令行参数中是否包含--model-path
+    args = sys.argv[1:]
+    has_model_path_arg = False
+
+    for i, arg in enumerate(args):
+        if arg == "--model-path" or arg.startswith("--model-path="):
+            has_model_path_arg = True
+            break
+
+    # 如果没有--model-path参数，在参数列表中添加它
+    if not has_model_path_arg:
+        default_path = auto_download_and_get_model_root_path("/", "vlm")
+        args.extend(["--model-path", default_path])
+
+    server_args = prepare_server_args(args)
 
     if server_args.chat_template is None:
         server_args.chat_template = "chatml"
 
     server_args.enable_custom_logit_processor = True
 
-    if server_args.model_path is None:
-        server_args.model_path = auto_download_and_get_model_root_path("/","vlm")
-
     try:
         launch_server(server_args)
     finally:

mineru/utils/config_reader.py

@@ -17,7 +17,7 @@ def read_config():
         config_file = os.path.join(home_dir, CONFIG_FILE_NAME)
 
     if not os.path.exists(config_file):
-        logger.warning(f'{config_file} not found, using default configuration')
+        # logger.warning(f'{config_file} not found, using default configuration')
         return None
     else:
         with open(config_file, 'r', encoding='utf-8') as f:
@@ -106,7 +106,9 @@ def get_formula_config():
 
 def get_latex_delimiter_config():
     config = read_config()
-    latex_delimiter_config = config.get('latex-delimiter-config')
+    if config is None:
+        return None
+    latex_delimiter_config = config.get('latex-delimiter-config', None)
     if latex_delimiter_config is None:
         # logger.warning(f"'latex-delimiter-config' not found in {CONFIG_FILE_NAME}, use 'None' as default")
         return None
@@ -116,7 +118,9 @@ def get_latex_delimiter_config():
 
 def get_llm_aided_config():
     config = read_config()
-    llm_aided_config = config.get('llm-aided-config')
+    if config is None:
+        return None
+    llm_aided_config = config.get('llm-aided-config', None)
     if llm_aided_config is None:
         # logger.warning(f"'llm-aided-config' not found in {CONFIG_FILE_NAME}, use 'None' as default")
         return None
@@ -126,6 +130,8 @@ def get_llm_aided_config():
 
 def get_local_models_dir():
     config = read_config()
+    if config is None:
+        return None
     models_dir = config.get('models-dir')
     if models_dir is None:
         logger.warning(f"'models-dir' not found in {CONFIG_FILE_NAME}, use None as default")

mineru/utils/draw_bbox.py

@@ -188,7 +188,8 @@ def draw_layout_bbox(pdf_info, pdf_bytes, out_path, filename):
             page.merge_page(overlay_pdf.pages[0])
         else:
             # 记录日志并继续处理下一个页面
-            logger.warning(f"layout.pdf: 第{i + 1}页未能生成有效的overlay PDF")
+            # logger.warning(f"layout.pdf: 第{i + 1}页未能生成有效的overlay PDF")
+            pass
 
         output_pdf.add_page(page)
 
@@ -302,7 +303,8 @@ def draw_span_bbox(pdf_info, pdf_bytes, out_path, filename):
             page.merge_page(overlay_pdf.pages[0])
         else:
             # 记录日志并继续处理下一个页面
-            logger.warning(f"span.pdf: 第{i + 1}页未能生成有效的overlay PDF")
+            # logger.warning(f"span.pdf: 第{i + 1}页未能生成有效的overlay PDF")
+            pass
 
         output_pdf.add_page(page)
 

mineru/utils/models_download_utils.py

@@ -51,9 +51,17 @@ def auto_download_and_get_model_root_path(relative_path: str, repo_mode='pipelin
     else:
         raise ValueError(f"未知的仓库类型: {model_source}")
 
-    relative_path = relative_path.strip('/')
-    cache_dir = snapshot_download(repo, allow_patterns=[relative_path, relative_path+"/*"])
+    cache_dir = None
 
+    if repo_mode == 'pipeline':
+        relative_path = relative_path.strip('/')
+        cache_dir = snapshot_download(repo, allow_patterns=[relative_path, relative_path+"/*"])
+    elif repo_mode == 'vlm':
+        # VLM 模式下，直接下载整个模型目录
+        cache_dir = snapshot_download(repo)
+
+    if not cache_dir:
+        raise FileNotFoundError(f"Failed to download model: {relative_path} from {repo}")
     return cache_dir
 
 

mineru/utils/ocr_utils.py

@@ -4,6 +4,11 @@ import cv2
 import numpy as np
 
 
+class OcrConfidence:
+    min_confidence = 0.68
+    min_width = 3
+
+
 def merge_spans_to_line(spans, threshold=0.6):
     if len(spans) == 0:
         return []
@@ -304,7 +309,7 @@ def get_ocr_result_list(ocr_res, useful_list, ocr_enable, new_image, lang):
             p1, p2, p3, p4 = box_ocr_res[0]
             text, score = box_ocr_res[1]
             # logger.info(f"text: {text}, score: {score}")
-            if score < 0.6:  # 过滤低置信度的结果
+            if score < OcrConfidence.min_confidence:  # 过滤低置信度的结果
                 continue
         else:
             p1, p2, p3, p4 = box_ocr_res
@@ -317,6 +322,11 @@ def get_ocr_result_list(ocr_res, useful_list, ocr_enable, new_image, lang):
         # average_angle_degrees = calculate_angle_degrees(box_ocr_res[0])
         # if average_angle_degrees > 0.5:
         poly = [p1, p2, p3, p4]
+
+        if (p3[0] - p1[0]) < OcrConfidence.min_width:
+            # logger.info(f"width too small: {p3[0] - p1[0]}, text: {text}")
+            continue
+
         if calculate_is_angle(poly):
             # logger.info(f"average_angle_degrees: {average_angle_degrees}, text: {text}")
             # 与x轴的夹角超过0.5度，对边界做一下矫正

next_docs/en/.readthedocs.yaml

-version: 2
-
-build:
-  os: ubuntu-22.04
-  tools:
-    python: "3.10"
-
-formats:
-  - epub
-
-python:
-  install:
-    - requirements: next_docs/requirements.txt
-
-sphinx:
-  configuration: next_docs/en/conf.py

next_docs/en/Makefile

-# Minimal makefile for Sphinx documentation
-#
-
-# You can set these variables from the command line, and also
-# from the environment for the first two.
-SPHINXOPTS    ?=
-SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
-
-# Put it first so that "make" without argument is like "make help".
-help:
-	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
-
-.PHONY: help Makefile
-
-# Catch-all target: route all unknown targets to Sphinx using the new
-# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

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