fix aws
Browse files- mineru_single.py +14 -13
mineru_single.py
CHANGED
@@ -30,22 +30,22 @@ class Processor:
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endpoint_url=os.getenv("S3_ENDPOINT"),
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)
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self.svm_model = SVMModel()
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logger.info("Classification model initialized successfully")
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with open("/home/user/magic-pdf.json", "r") as f:
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config = json.load(f)
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self.layout_mode = "doclayout_yolo"
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-
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self.formula_enable = config["formula-config"]["enable"]
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self.table_enable = config["table-config"]["enable"]
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self.language = "en"
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endpoint = os.getenv("S3_ENDPOINT", "").rstrip("/")
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bucket = os.getenv("S3_BUCKET_NAME", "")
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self.prefix = f"
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logger.info("Processor initialized successfully")
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except Exception as e:
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@@ -92,7 +92,7 @@ class Processor:
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logger.info("doc_analyze complete for key='%s'. Started extracting images...", key)
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# Classify images and remove irrelevant ones
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-
image_writer = ImageWriter(self.s3_writer
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pipe_result = inference.pipe_ocr_mode(image_writer, lang=self.language)
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logger.info("OCR pipeline completed for key='%s'.", key)
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@@ -109,21 +109,22 @@ class ImageWriter(DataWriter):
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Receives each extracted image. Classifies it, uploads if relevant, or flags
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it for removal if irrelevant.
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"""
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def __init__(self, s3_writer: S3Writer
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self.s3_writer = s3_writer
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self.svm_model = svm_model
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self._redundant_images_paths = []
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def write(self, path: str, data: bytes) -> None:
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"""
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Called for each extracted image. If relevant, upload to S3; otherwise mark for removal.
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"""
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if label_str == 1:
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else:
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def remove_redundant_images(self, md_content: str) -> str:
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for path in self._redundant_images_paths:
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endpoint_url=os.getenv("S3_ENDPOINT"),
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)
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+
# self.svm_model = SVMModel()
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+
# logger.info("Classification model initialized successfully")
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with open("/home/user/magic-pdf.json", "r") as f:
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config = json.load(f)
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+
# self.layout_mode = "doclayout_yolo"
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+
self.layout_mode = config["layout-config"]["model"]
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self.formula_enable = config["formula-config"]["enable"]
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self.table_enable = config["table-config"]["enable"]
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self.language = "en"
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endpoint = os.getenv("S3_ENDPOINT", "").rstrip("/")
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bucket = os.getenv("S3_BUCKET_NAME", "")
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self.prefix = f"/document-extracts/"
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logger.info("Processor initialized successfully")
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except Exception as e:
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logger.info("doc_analyze complete for key='%s'. Started extracting images...", key)
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# Classify images and remove irrelevant ones
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+
image_writer = ImageWriter(self.s3_writer)
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pipe_result = inference.pipe_ocr_mode(image_writer, lang=self.language)
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logger.info("OCR pipeline completed for key='%s'.", key)
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Receives each extracted image. Classifies it, uploads if relevant, or flags
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it for removal if irrelevant.
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"""
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+
def __init__(self, s3_writer: S3Writer):
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self.s3_writer = s3_writer
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# self.svm_model = svm_model
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self._redundant_images_paths = []
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def write(self, path: str, data: bytes) -> None:
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"""
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Called for each extracted image. If relevant, upload to S3; otherwise mark for removal.
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"""
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self.s3_writer.write(path, data)
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# label_str = self.svm_model.classify_image(data)
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# if label_str == 1:
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# else:
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# self._redundant_images_paths.append(path)
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def remove_redundant_images(self, md_content: str) -> str:
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for path in self._redundant_images_paths:
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