Image Caption accepts bytes for images (#12561)

Accept bytes for images in image caption

---------

Co-authored-by: webcoderz <19884161+webcoderz@users.noreply.github.com>
pull/12569/head
Eugene Yurtsev 10 months ago committed by GitHub
parent 7897483819
commit 1b1a2d5740
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GPG Key ID: 4AEE18F83AFDEB23

@ -1,3 +1,4 @@
from io import BytesIO
from typing import Any, List, Tuple, Union from typing import Any, List, Tuple, Union
import requests import requests
@ -16,30 +17,28 @@ class ImageCaptionLoader(BaseLoader):
def __init__( def __init__(
self, self,
path_images: Union[str, List[str]], images: Union[str, bytes, List[Union[str, bytes]]],
blip_processor: str = "Salesforce/blip-image-captioning-base", blip_processor: str = "Salesforce/blip-image-captioning-base",
blip_model: str = "Salesforce/blip-image-captioning-base", blip_model: str = "Salesforce/blip-image-captioning-base",
): ):
""" """Initialize with a list of image data (bytes) or file paths
Initialize with a list of image paths
Args: Args:
path_images: A list of image paths. images: Either a single image or a list of images. Accepts
image data (bytes) or file paths to images.
blip_processor: The name of the pre-trained BLIP processor. blip_processor: The name of the pre-trained BLIP processor.
blip_model: The name of the pre-trained BLIP model. blip_model: The name of the pre-trained BLIP model.
""" """
if isinstance(path_images, str): if isinstance(images, (str, bytes)):
self.image_paths = [path_images] self.images = [images]
else: else:
self.image_paths = path_images self.images = images
self.blip_processor = blip_processor self.blip_processor = blip_processor
self.blip_model = blip_model self.blip_model = blip_model
def load(self) -> List[Document]: def load(self) -> List[Document]:
""" """Load from a list of image data or file paths"""
Load from a list of image files
"""
try: try:
from transformers import BlipForConditionalGeneration, BlipProcessor from transformers import BlipForConditionalGeneration, BlipProcessor
except ImportError: except ImportError:
@ -52,9 +51,9 @@ class ImageCaptionLoader(BaseLoader):
model = BlipForConditionalGeneration.from_pretrained(self.blip_model) model = BlipForConditionalGeneration.from_pretrained(self.blip_model)
results = [] results = []
for path_image in self.image_paths: for image in self.images:
caption, metadata = self._get_captions_and_metadata( caption, metadata = self._get_captions_and_metadata(
model=model, processor=processor, path_image=path_image model=model, processor=processor, image=image
) )
doc = Document(page_content=caption, metadata=metadata) doc = Document(page_content=caption, metadata=metadata)
results.append(doc) results.append(doc)
@ -62,11 +61,9 @@ class ImageCaptionLoader(BaseLoader):
return results return results
def _get_captions_and_metadata( def _get_captions_and_metadata(
self, model: Any, processor: Any, path_image: str self, model: Any, processor: Any, image: Union[str, bytes]
) -> Tuple[str, dict]: ) -> Tuple[str, dict]:
""" """Helper function for getting the captions and metadata of an image."""
Helper function for getting the captions and metadata of an image
"""
try: try:
from PIL import Image from PIL import Image
except ImportError: except ImportError:
@ -74,20 +71,29 @@ class ImageCaptionLoader(BaseLoader):
"`PIL` package not found, please install with `pip install pillow`" "`PIL` package not found, please install with `pip install pillow`"
) )
image_source = image # Save the original source for later reference
try: try:
if path_image.startswith("http://") or path_image.startswith("https://"): if isinstance(image, bytes):
image = Image.open(requests.get(path_image, stream=True).raw).convert( image = Image.open(BytesIO(image)).convert("RGB")
"RGB" elif image.startswith("http://") or image.startswith("https://"):
) image = Image.open(requests.get(image, stream=True).raw).convert("RGB")
else: else:
image = Image.open(path_image).convert("RGB") image = Image.open(image).convert("RGB")
except Exception: except Exception:
raise ValueError(f"Could not get image data for {path_image}") if isinstance(image_source, bytes):
msg = "Could not get image data from bytes"
else:
msg = f"Could not get image data for {image_source}"
raise ValueError(msg)
inputs = processor(image, "an image of", return_tensors="pt") inputs = processor(image, "an image of", return_tensors="pt")
output = model.generate(**inputs) output = model.generate(**inputs)
caption: str = processor.decode(output[0]) caption: str = processor.decode(output[0])
metadata: dict = {"image_path": path_image} if isinstance(image_source, bytes):
metadata: dict = {"image_source": "Image bytes provided"}
else:
metadata = {"image_path": image_source}
return caption, metadata return caption, metadata

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