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remove references to PDF reading via PIL (#15293)

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* fix confusing PIL instructions

As stated in the documentation
[here](https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html?highlight=pdf#write-only-formats),
PIL can only write PDF's, not read them. Remove references to reading
PDF's via PIL from this page to avoid confusion.

* mention PDF in doc examples using PIL

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Be explicit: PDFs must be converted to images

* fix formatting

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
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Nathan Glenn 2022-03-28 02:00:29 -07:00 committed by GitHub
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24
docs/source/model_doc/layoutlmv2.mdx
View file

@ -85,7 +85,9 @@ follows:
```python
from PIL import Image
image = Image.open("name_of_your_document - can be a png file, pdf, etc.")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
)
width, height = image.size
```
@ -157,7 +159,9 @@ from PIL import Image
processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased")
image = Image.open("name_of_your_document - can be a png file, pdf, etc.").convert("RGB")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
).convert("RGB")
encoding = processor(
image, return_tensors="pt"
) # you can also add all tokenizer parameters here such as padding, truncation
@ -177,7 +181,9 @@ from PIL import Image
processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased", revision="no_ocr")
image = Image.open("name_of_your_document - can be a png file, pdf, etc.").convert("RGB")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
).convert("RGB")
words = ["hello", "world"]
boxes = [[1, 2, 3, 4], [5, 6, 7, 8]] # make sure to normalize your bounding boxes
encoding = processor(image, words, boxes=boxes, return_tensors="pt")
@ -199,7 +205,9 @@ from PIL import Image
processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased", revision="no_ocr")
image = Image.open("name_of_your_document - can be a png file, pdf, etc.").convert("RGB")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
).convert("RGB")
words = ["hello", "world"]
boxes = [[1, 2, 3, 4], [5, 6, 7, 8]] # make sure to normalize your bounding boxes
word_labels = [1, 2]
@ -219,7 +227,9 @@ from PIL import Image
processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased")
image = Image.open("name_of_your_document - can be a png file, pdf, etc.").convert("RGB")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
).convert("RGB")
question = "What's his name?"
encoding = processor(image, question, return_tensors="pt")
print(encoding.keys())
@ -237,7 +247,9 @@ from PIL import Image
processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased", revision="no_ocr")
image = Image.open("name_of_your_document - can be a png file, pdf, etc.").convert("RGB")
image = Image.open(
"name_of_your_document - can be a png, jpg, etc. of your documents (PDFs must be converted to images)."
).convert("RGB")
question = "What's his name?"
words = ["hello", "world"]
boxes = [[1, 2, 3, 4], [5, 6, 7, 8]] # make sure to normalize your bounding boxes