DEEPSEEK-OCR RESULTS ZIP FILE
==============================

This zip file contains all scripts, documentation, and OCR results from the 
DeepSeek-OCR setup project on NVIDIA GB10 (ARM64 + CUDA 13.0).

EXCLUDED (Large Files):
- DeepSeek-OCR/ (GitHub repository)
- DeepSeek-OCR-model/ (6.3GB HuggingFace model)

To use these scripts, you'll need to:
1. Run setup.sh to clone repositories and install dependencies
2. Model will be cloned from HuggingFace automatically

CONTENTS:
=========

DOCUMENTATION (8 files, 58KB):
------------------------------
FINAL_SUMMARY.md         - Complete project overview
PROMPTS_GUIDE.md         - Guide to different OCR prompts
README.md                - Original comprehensive setup guide
README_SUCCESS.md        - Quick start guide
SOLUTION.md              - PyTorch 2.9.0+cu130 solution details
TEXT_OUTPUT_SUMMARY.md   - Text output improvements
UPDATE_PYTORCH.md        - Upgrade instructions
notes.md                 - Detailed chronological setup notes

SCRIPTS (6 files):
------------------
setup.sh                 - Install all dependencies (PyTorch 2.9.0+cu130)
download_test_image.sh   - Download test image
run_ocr.py               - Main OCR with bounding boxes
run_ocr.sh               - Convenience wrapper
run_ocr_best.py          - Best text output (uses "Free OCR" prompt)
run_ocr_cpu_nocuda.py    - CPU fallback version
run_ocr_text_focused.py  - Tests all prompt types

OCR OUTPUTS:
------------
output/
  result_with_boxes.jpg  - Original grounding mode (bounding boxes)
  result.mmd             - (mostly whitespace - grounding mode)

output_text/
  free_ocr/
    result.mmd           - Clean text output ⭐ RECOMMENDED
    result_with_boxes.jpg
  
  markdown/
    result.mmd           - Structured markdown output
    result_with_boxes.jpg
    images/0.jpg         - Extracted image
  
  detailed/
    result.mmd           - Image description (not OCR)
    result_with_boxes.jpg

TEST IMAGE:
-----------
test_image.jpeg          - Financial Times article (586KB)

QUICK START:
============

1. Extract this zip file
2. Read README_SUCCESS.md for quick start
3. For best text OCR: python3 run_ocr_best.py test_image.jpeg
4. For setup: bash setup.sh (clones repos and installs deps)

KEY FINDINGS:
=============

✅ PyTorch 2.9.0+cu130 works with NVIDIA GB10 (sm_121)
✅ Use "Free OCR" prompt for best text output
✅ Use "Grounding OCR" for bounding boxes
✅ OCR inference: 24-58 seconds depending on prompt

FILE SIZE: ~4MB (compressed from ~4.3MB uncompressed)
DATE: 2025-10-20
PLATFORM: NVIDIA GB10 (ARM64) + CUDA 13.0 + Docker
