fix(doc-analyze): adjust image scaling limit to 9000 pixels

Previously, images were not enlarged if their width or height exceeded 3000 pixels.
This threshold has been increased to 9000 pixels to better handle high-resolutionscans and improve the analysis of documents with larger dimensions.

fix&refactor(pdf-extract-kit):  table recognition and ocr

fix(pdf-extract-kit): ensure table extraction success with additional ending conditionAdd an additional condition to determine the success of table extraction by checking
if the latex_code ends with 'end{table}'. This extends the validation to cover table
environments that may not strictly end with 'end{tabular}', thus improving the robustnessof table recognition processing.

refactor(pdf_extract_kit): optimize image processing and table recognition logicRefactor the image processing logic for OCR and table recognition to ensure
consistency and improve performance. Remove redundant initialization of PIL images,
unify image cropping logic, and streamline the handling of formula detection results.
Also, adjust the table recognition process to improve integration with the updated image
processing logic and enhance overall efficiency.

Co-authored-by: shenguanlin <shenguanlin@pjlab.org.cn>

Add notes in the Ubuntu and Windows CUDA acceleration guides on how to
determine if CUDA acceleration is working. This includes checking for
significant reductions in `layout detection cost`, `mfr time`, and `ocr cost`
as indicators of successful acceleration.

feat: add table recognition success detect

Add an exclamation mark to the section title to stress the importance of completing the
additional steps after downloading a model. This change is made in the Chinese
documentation to ensure users are aware of the necessary post-download actions.

Adjust the print statement in the how_to_download_models_zh_cn.md guide to reflect
the correct model download location. The path has been updated to specify the 'models'
directory where the model is actually downloaded.

feat: add table recognition success detect

Add a print statement to the example code in 'how_to_download_models_zh_cn.md' to
output the downloaded model directory path. This enhancement aids users in locating
the model files as it provides a clear indication of where they are saved on the
user's file system.

docs(readme): update acknowledgment section and project description- Streamline the Acknowledgments section in the README by removing redundant entries.- Clarify the project's current use of PyMuPDF and future plans for exploring a more  permissively licensed PDF processing library in the project description.
- Ensure all modifications adhere to the project's documentation standards and improve reader understanding.

docs(readme): update acknowledgment section and project description- Streamline the Acknowledgments section in the README by removing redundant entries.- Clarify the project's current use of PyMuPDF and future plans for exploring a more  permissively licensed PDF processing library in the project description.
- Ensure all modifications adhere to the project's documentation standards and improve reader understanding.

docs(models-download): update steps and remove deprecated sectionsUpdate the model download instructions to reflect the current process, removing
unnecessary sections and simplifying the steps. The updated guide now includesclearer instructions on installing Git LFS, downloading models from Hugging Face,and additional checks for model file completeness. This change ensures that the
documentation is up-to-date and provides a streamlined experience for users
downloading models.

docs: correct path format description in Windows CUDA docsUpdate the instructions in the Windows CUDA Acceleration documentation toreflect the correct path format. Specifically, clarify that Windows paths
should include the drive letter and replace backslashes with forward slashes.

Update the URLs for downloading the `magic-pdf.template.json` and `small_ocr.pdf`
files in the Windows CUDA acceleration guides. The links now point to the giteerepository instead of GitHub, ensuring users have access to the necessary files
from the correct source.

- Streamline the installation process by removing the redundant apt update step.
- Adjust the numbering of installation steps throughout the document.
- Update download URLs to gitee for the configuration template and demo file.
- Ensure consistency in the model directory configuration advice.

Add a new README_Ubuntu_CUDA_Acceleration_en_US.md document to provide users with a
setup guide for enabling and testing CUDA acceleration on Ubuntu 22.04 LTS. The guideincludes steps to check and install NVIDIA drivers, install Anaconda, create a conda
environment, install required applications, download and verify models, configure theenvironment, and test CUDA acceleration.

This addition addresses the need for clear, concise instructions on achieving better
performance with CUDA-enabled graphics cards and

- Note the fix in version 0.6.2b1 for the network error during the first run of offline  deployment and clarify the model download requirement.
- Update the dependency installation guide for users on macOS with Intel CPUs.
- Indicate the resolution in version 0.6.2b1 for compatibility issues with paddlepaddle
  version 2.6.1 on certain Linux systems.

This change aims to make the FAQ more informative and easier to navigate for users
experiencing similar issues, providing direct solutions and links where applicable.

docs: add conda install steps for environment setupAdd detailed steps on how to create a conda environment and activate it beforeproceeding with the pip installation of magic-pdf and required dependencies.
This provides users with a clearer guide on setting up their environment.