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Fixing object detection with layoutlm (#20776)

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* Fixing object detection with layoutlm.

* Fixup.
This commit is contained in:
Nicolas Patry
2022-12-15 18:46:43 +01:00
committed by GitHub
parent 8891193e83
commit fca66abe2a
2 changed files with 9 additions and 12 deletions
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7
src/transformers/pipelines/__init__.py
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@@ -378,7 +378,12 @@ NO_TOKENIZER_TASKS = set()
# any tokenizer/feature_extractor might be use for a given model so we cannot # any tokenizer/feature_extractor might be use for a given model so we cannot
# use the statically defined TOKENIZER_MAPPING and FEATURE_EXTRACTOR_MAPPING to # use the statically defined TOKENIZER_MAPPING and FEATURE_EXTRACTOR_MAPPING to
# see if the model defines such objects or not. # see if the model defines such objects or not.
MULTI_MODEL_CONFIGS = {"SpeechEncoderDecoderConfig", "VisionEncoderDecoderConfig", "VisionTextDualEncoderConfig"} MULTI_MODEL_CONFIGS = {
"SpeechEncoderDecoderConfig",
"VisionEncoderDecoderConfig",
"VisionTextDualEncoderConfig",
"LayoutLMConfig",
}
for task, values in SUPPORTED_TASKS.items(): for task, values in SUPPORTED_TASKS.items():
if values["type"] == "text": if values["type"] == "text":
NO_FEATURE_EXTRACTOR_TASKS.add(task) NO_FEATURE_EXTRACTOR_TASKS.add(task)

14
tests/pipelines/test_pipelines_object_detection.py
View File

@@ -256,17 +256,9 @@ class ObjectDetectionPipelineTests(unittest.TestCase, metaclass=PipelineTestCase
"https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png" "https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"
) )
self.assertEqual( self.assertEqual(
nested_simplify(outputs, decimals=4), nested_simplify(outputs, decimals=3),
[ [
{ {"score": 0.998, "label": "B-QUESTION", "box": {"xmin": 462, "ymin": 234, "xmax": 508, "ymax": 249}},
"score": 0.9982, {"score": 0.999, "label": "I-QUESTION", "box": {"xmin": 489, "ymin": 286, "xmax": 519, "ymax": 301}},
"label": "B-QUESTION",
"box": {"xmin": 654, "ymin": 165, "xmax": 719, "ymax": 719},
},
{
"score": 0.9982,
"label": "I-QUESTION",
"box": {"xmin": 691, "ymin": 202, "xmax": 735, "ymax": 735},
},
], ],
) )