Merge pull request #906 from icecraft/feat/add_en_docs

Feat/add en docs

docs/en/additional_notes/known_issues.rst

+Known Issues
+============
+
+-  Reading order is determined by the model based on the spatial
+   distribution of readable content, and may be out of order in some
+   areas under extremely complex layouts.
+-  Vertical text is not supported.
+-  Tables of contents and lists are recognized through rules, and some
+   uncommon list formats may not be recognized.
+-  Only one level of headings is supported; hierarchical headings are
+   not currently supported.
+-  Code blocks are not yet supported in the layout model.
+-  Comic books, art albums, primary school textbooks, and exercises
+   cannot be parsed well.
+-  Table recognition may result in row/column recognition errors in
+   complex tables.
+-  OCR recognition may produce inaccurate characters in PDFs of
+   lesser-known languages (e.g., diacritical marks in Latin script,
+   easily confused characters in Arabic script).
+-  Some formulas may not render correctly in Markdown.
\ No newline at end of file

next_docs/en/index.rst → docs/en/index.rst

@@ -46,20 +46,29 @@ the relevant PDF**.
 Key Features
 ------------
 
--  Removes elements such as headers, footers, footnotes, and page
-   numbers while maintaining semantic continuity
--  Outputs text in a human-readable order from multi-column documents
--  Retains the original structure of the document, including titles,
-   paragraphs, and lists
--  Extracts images, image captions, tables, and table captions
--  Automatically recognizes formulas in the document and converts them
-   to LaTeX
--  Automatically recognizes tables in the document and converts them to
-   LaTeX
--  Automatically detects and enables OCR for corrupted PDFs
--  Supports both CPU and GPU environments
--  Supports Windows, Linux, and Mac platforms
-
+-  Remove headers, footers, footnotes, page numbers, etc., to ensure
+   semantic coherence.
+-  Output text in human-readable order, suitable for single-column,
+   multi-column, and complex layouts.
+-  Preserve the structure of the original document, including headings,
+   paragraphs, lists, etc.
+-  Extract images, image descriptions, tables, table titles, and
+   footnotes.
+-  Automatically recognize and convert formulas in the document to LaTeX
+   format.
+-  Automatically recognize and convert tables in the document to LaTeX
+   or HTML format.
+-  Automatically detect scanned PDFs and garbled PDFs and enable OCR
+   functionality.
+-  OCR supports detection and recognition of 84 languages.
+-  Supports multiple output formats, such as multimodal and NLP
+   Markdown, JSON sorted by reading order, and rich intermediate
+   formats.
+-  Supports various visualization results, including layout
+   visualization and span visualization, for efficient confirmation of
+   output quality.
+-  Supports both CPU and GPU environments.
+-  Compatible with Windows, Linux, and Mac platforms.
 
 User Guide
 -------------
@@ -91,14 +100,6 @@ Additional Notes
 
    additional_notes/known_issues
    additional_notes/faq
-   additional_notes/changelog
    additional_notes/glossary
 
 
-Projects 
----------
-.. toctree::
-   :maxdepth: 1
-   :caption: Projects
-
-   projects
\ No newline at end of file

next_docs/en/user_guide/install/boost_with_cuda.rst → docs/en/user_guide/install/boost_with_cuda.rst

@@ -137,7 +137,7 @@ Download a sample file from the repository and test it.
 .. code:: sh
 
    wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
-   magic-pdf -p small_ocr.pdf
+   magic-pdf -p small_ocr.pdf -o ./output
 
 9. Test CUDA Acceleration
 ~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -145,10 +145,6 @@ Download a sample file from the repository and test it.
 If your graphics card has at least **8GB** of VRAM, follow these steps
 to test CUDA acceleration:
 
-   ❗ Due to the extremely limited nature of 8GB VRAM for running this
-   application, you need to close all other programs using VRAM to
-   ensure that 8GB of VRAM is available when running this application.
-
 1. Modify the value of ``"device-mode"`` in the ``magic-pdf.json``
    configuration file located in your home directory.
 
@@ -162,7 +158,7 @@ to test CUDA acceleration:
 
    .. code:: sh
 
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
 
 10. Enable CUDA Acceleration for OCR
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -178,7 +174,9 @@ to test CUDA acceleration:
 
    .. code:: sh
 
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
+
+
 
 .. _windows_10_or_11_section:
 
@@ -252,7 +250,7 @@ Download a sample file from the repository and test it.
 .. code:: powershell
 
      wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
-     magic-pdf -p small_ocr.pdf
+     magic-pdf -p small_ocr.pdf -o ./output
 
 8. Test CUDA Acceleration
 ~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -260,10 +258,6 @@ Download a sample file from the repository and test it.
 If your graphics card has at least 8GB of VRAM, follow these steps to
 test CUDA-accelerated parsing performance.
 
-   ❗ Due to the extremely limited nature of 8GB VRAM for running this
-   application, you need to close all other programs using VRAM to
-   ensure that 8GB of VRAM is available when running this application.
-
 1. **Overwrite the installation of torch and torchvision** supporting
    CUDA.
 
@@ -295,7 +289,7 @@ test CUDA-accelerated parsing performance.
 
    ::
 
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
 
 9. Enable CUDA Acceleration for OCR
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -311,5 +305,4 @@ test CUDA-accelerated parsing performance.
 
    ::
 
-      magic-pdf -p small_ocr.pdf
-
+      magic-pdf -p small_ocr.pdf -o ./output