Add Aryn trained DETR model for entity detection #212
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bohou-aryn
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| def zero(self) -> bool: | ||
| return math.isclose(self.x1, self.x2, rel_tol=1e-6) or math.isclose(self.y1, self.y2, rel_tol=1e-6) | ||
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| def iou(self, other: "BoundingBox") -> float: |
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Minor: This is "intersection over union", right? Maybe leave a comment so people know what to search for.
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| @staticmethod | ||
| def _supplement_text(inferred: List[Element], text: List[Element], threshold: float = 0.5) -> List[Element]: | ||
| # this is a n^2 time complexity, but for hungarian, it's too expensive? n^3 |
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Can you give a little more context here on your choices? From Googling I see that the Hungarian algorithm is indeed O(n^3), but it's not very clear to me what algorithm we used that is O(n^2). Is it the same as Unstructured? What are the cases where this doesn't work?
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fixed, similar but simplified, I only supplement text element to the inferred ones.
| return inferred | ||
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| def partition_pdf(self, file: BinaryIO, threshold: float = 0.4) -> List[List["Element"]]: | ||
| with tempfile.TemporaryDirectory() as tmp_dir, tempfile.NamedTemporaryFile() as tmp_file: |
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Do we write to a temporary file because pdf2image/pdfminer/detr expect it? Do they only support names, or can you pass in a BinaryIO object? I know pd2image supports binary (
sycamore/sycamore/functions/document.py
Line 38 in 725adf8
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I did not make it work directly from bytes, would try couple more times.
| results = self.processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=threshold)[ | ||
| 0 | ||
| ] |
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I guess since this passes linting this must be what black generated, right? What a weird format for array indexing :)
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