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test: validate actual docitems in tests (#966)
* validate actual docitems in tests Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * remove verbose print Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * disable test generation Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> --------- Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
This commit is contained in:
Michele Dolfi
GitHub
@@ -1,10 +1,17 @@
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import json
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import warnings
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from pathlib import Path
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from typing import List
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from typing import List, Optional
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from docling_core.types.doc import DoclingDocument
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from docling_core.types.doc import (
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DocItem,
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DoclingDocument,
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PictureItem,
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TableItem,
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TextItem,
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)
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from docling_core.types.legacy_doc.document import ExportedCCSDocument as DsDocument
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from PIL import Image as PILImage
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from pydantic import TypeAdapter
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from pydantic.json import pydantic_encoder
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@@ -153,64 +160,58 @@ def verify_tables_v1(doc_pred: DsDocument, doc_true: DsDocument, fuzzy: bool):
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return True
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def verify_tables_v2(doc_pred: DoclingDocument, doc_true: DoclingDocument, fuzzy: bool):
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if not len(doc_true.tables) > 0:
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# No tables to check
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assert len(doc_pred.tables) == 0, "not expecting any table on this document"
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return True
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else:
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assert len(doc_pred.tables) > 0, "no tables predicted, but expected in doc_true"
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def verify_table_v2(true_item: TableItem, pred_item: TableItem, fuzzy: bool):
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assert (
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true_item.data.num_rows == pred_item.data.num_rows
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), "table does not have the same #-rows"
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assert (
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true_item.data.num_cols == pred_item.data.num_cols
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), "table does not have the same #-cols"
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# print("Expected number of tables: {}, result: {}".format(len(doc_true.tables), len(doc_pred.tables)))
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assert true_item.data is not None, "documents are expected to have table data"
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assert pred_item.data is not None, "documents are expected to have table data"
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assert len(doc_true.tables) == len(
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doc_pred.tables
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), "document has different count of tables than expected."
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# print("True: \n", true_item.export_to_dataframe().to_markdown())
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# print("Pred: \n", true_item.export_to_dataframe().to_markdown())
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for l, true_item in enumerate(doc_true.tables):
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pred_item = doc_pred.tables[l]
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for i, row in enumerate(true_item.data.grid):
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for j, col in enumerate(true_item.data.grid[i]):
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assert (
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true_item.data.num_rows == pred_item.data.num_rows
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), "table does not have the same #-rows"
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assert (
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true_item.data.num_cols == pred_item.data.num_cols
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), "table does not have the same #-cols"
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# print("true: ", true_item.data[i][j].text)
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# print("pred: ", pred_item.data[i][j].text)
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# print("")
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assert true_item.data is not None, "documents are expected to have table data"
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assert pred_item.data is not None, "documents are expected to have table data"
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verify_text(
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true_item.data.grid[i][j].text,
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pred_item.data.grid[i][j].text,
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fuzzy=fuzzy,
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)
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print("True: \n", true_item.export_to_dataframe().to_markdown())
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print("Pred: \n", true_item.export_to_dataframe().to_markdown())
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assert (
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true_item.data.grid[i][j].column_header
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== pred_item.data.grid[i][j].column_header
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), "table-cell should be a column_header but prediction isn't"
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for i, row in enumerate(true_item.data.grid):
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for j, col in enumerate(true_item.data.grid[i]):
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assert (
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true_item.data.grid[i][j].row_header
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== pred_item.data.grid[i][j].row_header
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), "table-cell should be a row_header but prediction isn't"
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# print("true: ", true_item.data[i][j].text)
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# print("pred: ", pred_item.data[i][j].text)
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# print("")
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assert (
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true_item.data.grid[i][j].row_section
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== pred_item.data.grid[i][j].row_section
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), "table-cell should be a row_section but prediction isn't"
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verify_text(
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true_item.data.grid[i][j].text,
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pred_item.data.grid[i][j].text,
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fuzzy=fuzzy,
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)
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return True
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assert (
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true_item.data.grid[i][j].column_header
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== pred_item.data.grid[i][j].column_header
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), "table-cell should be a column_header but prediction isn't"
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assert (
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true_item.data.grid[i][j].row_header
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== pred_item.data.grid[i][j].row_header
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), "table-cell should be a row_header but prediction isn't"
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assert (
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true_item.data.grid[i][j].row_section
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== pred_item.data.grid[i][j].row_section
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), "table-cell should be a row_section but prediction isn't"
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def verify_picture_image_v2(
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true_image: PILImage.Image, pred_item: Optional[PILImage.Image]
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):
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assert pred_item is not None, "predicted image is None"
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assert true_image.size == pred_item.size
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assert true_image.mode == pred_item.mode
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# assert true_image.tobytes() == pred_item.tobytes()
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return True
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@@ -220,6 +221,70 @@ def verify_tables_v2(doc_pred: DoclingDocument, doc_true: DoclingDocument, fuzzy
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# return True
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def verify_docitems(doc_pred: DoclingDocument, doc_true: DoclingDocument, fuzzy: bool):
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assert len(doc_pred.texts) == len(doc_true.texts), f"Text lengths do not match."
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assert len(doc_true.tables) == len(
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doc_pred.tables
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), "document has different count of tables than expected."
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for (true_item, _true_level), (pred_item, _pred_level) in zip(
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doc_true.iterate_items(), doc_pred.iterate_items()
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):
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if not isinstance(true_item, DocItem):
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continue
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assert isinstance(pred_item, DocItem), "Test item is not a DocItem"
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# Validate type
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assert true_item.label == pred_item.label, f"Object label does not match."
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# Validate provenance
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assert len(true_item.prov) == len(pred_item.prov), "Length of prov mismatch"
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if len(true_item.prov) > 0:
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true_prov = true_item.prov[0]
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pred_prov = pred_item.prov[0]
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assert true_prov.page_no == pred_prov.page_no, "Page provenance mistmatch"
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# TODO: add bbox check with tolerance
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# Validate text content
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if isinstance(true_item, TextItem):
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assert isinstance(pred_item, TextItem), (
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"Test item is not a TextItem as the expected one "
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f"{true_item=} "
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f"{pred_item=} "
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)
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assert verify_text(true_item.text, pred_item.text, fuzzy=fuzzy)
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# Validate table content
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if isinstance(true_item, TableItem):
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assert isinstance(
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pred_item, TableItem
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), "Test item is not a TableItem as the expected one"
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assert verify_table_v2(
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true_item, pred_item, fuzzy=fuzzy
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), "Tables not matching"
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# Validate picture content
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if isinstance(true_item, PictureItem):
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assert isinstance(
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pred_item, PictureItem
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), "Test item is not a PictureItem as the expected one"
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true_image = true_item.get_image(doc=doc_true)
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pred_image = true_item.get_image(doc=doc_pred)
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if true_image is not None:
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assert verify_picture_image_v2(
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true_image, pred_image
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), "Picture image mismatch"
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# TODO: check picture annotations
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return True
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def verify_md(doc_pred_md: str, doc_true_md: str, fuzzy: bool):
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return verify_text(doc_true_md, doc_pred_md, fuzzy)
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@@ -381,9 +446,9 @@ def verify_conversion_result_v2(
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# doc_pred, doc_true
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# ), f"Mismatch in JSON prediction for {input_path}"
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assert verify_tables_v2(
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assert verify_docitems(
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doc_pred, doc_true, fuzzy=fuzzy
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), f"verify_tables(doc_pred, doc_true) mismatch for {input_path}"
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), f"verify_docling_document(doc_pred, doc_true) mismatch for {input_path}"
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assert verify_md(
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doc_pred_md, doc_true_md, fuzzy=fuzzy
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