Marmelator/image-classification-service
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fixed chaining bug that lead to greedy evaluation

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This commit is contained in:
Matthias Bisping 2022-03-30 00:53:34 +02:00
parent 81ab9a5f53
commit 45a07c620a
4 changed files with 15 additions and 6 deletions
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5
image_prediction/classifier/image_classifier.py
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@ -22,7 +22,8 @@ class ImageClassifier:
def predict(self, images: Iterable[Image], batch_size=16): def predict(self, images: Iterable[Image], batch_size=16):
batches = chunk_iterable(images, chunk_size=batch_size) batches = chunk_iterable(images, chunk_size=batch_size)
return chain(*map(self.pipe, batches)) predictions = chain.from_iterable(map(self.pipe, batches))
return predictions
def __call__(self, images: Iterable[Image], batch_size=16): def __call__(self, images: Iterable[Image], batch_size=16):
return self.predict(images, batch_size=batch_size) yield from self.predict(images, batch_size=batch_size)

3
image_prediction/extractor_classifier/extractor_classifier.py
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@ -27,4 +27,5 @@ class ExtractorClassifier:
def __call__(self, obj) -> Iterable[ImageMetadataPair]: def __call__(self, obj) -> Iterable[ImageMetadataPair]:
image_metadata_pairs = self.extractor(obj) image_metadata_pairs = self.extractor(obj)
batches = chunk_iterable(image_metadata_pairs, chunk_size=16) batches = chunk_iterable(image_metadata_pairs, chunk_size=16)
return chain(*map(self.__process_batch, batches)) predictions = chain.from_iterable(map(self.__process_batch, batches))
return predictions

11
image_prediction/image_extractor/extractors/parsable.py
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@ -9,6 +9,9 @@ from tqdm import tqdm
from image_prediction.image_extractor.extractor import ImageExtractor, ImageMetadataPair from image_prediction.image_extractor.extractor import ImageExtractor, ImageMetadataPair
from image_prediction.info import Info from image_prediction.info import Info
from image_prediction.utils import get_logger
logger = get_logger()
class ParsablePDFImageExtractor(ImageExtractor): class ParsablePDFImageExtractor(ImageExtractor):
@ -47,8 +50,12 @@ class ParsablePDFImageExtractor(ImageExtractor):
return starmap(ImageMetadataPair, zip(images, metadata)) return starmap(ImageMetadataPair, zip(images, metadata))
def extract(self, pdf: bytes): def extract(self, pdf: bytes):
logger.debug("Extracting")
self.doc = fitz.Document(stream=pdf) self.doc = fitz.Document(stream=pdf)
image_metadata_pairs = chain(
*map(self.__process_images_on_page, tqdm(self.doc, desc="Extracting", disable=not self.verbose)) image_metadata_pairs = chain.from_iterable(
map(self.__process_images_on_page, tqdm(self.doc, desc="Extracting", disable=not self.verbose))
) )
return image_metadata_pairs return image_metadata_pairs

2
image_prediction/pipeline.py
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@ -51,4 +51,4 @@ class Pipeline:
self.pipe = rcompose(get_extractor_classifier(), get_formatter()) self.pipe = rcompose(get_extractor_classifier(), get_formatter())
def __call__(self, pdf: bytes): def __call__(self, pdf: bytes):
return self.pipe(pdf) yield from self.pipe(pdf)