pdf-image-table-cropper 0.1.1

Crop image/table/code regions from PDF files and export metadata

PDF Image Table Cropper

A pip-installable CLI + SDK tool that detects and crops image / table / code / algorithm regions from PDFs, then exports JPG files and metadata.json.

No OCR. No full-text extraction.

1. Install

Recommended for development:

pip install -e .

Or standard local install:

pip install .

Recommended Python version: >=3.10.

2. Quick Start

CLI mode after installation:

pdf-image-table-cropper \
  -i /path/to/paper.pdf \
  -o ./output

Output path: ./output/<pdf_stem>/.

3. Common Examples

Export table regions only, with selected pages:

pdf-image-table-cropper \
  -i paper.pdf \
  -o ./output \
  --type table \
  --pages 1-5,8,10

Default model (docling Heron, primary detector):

pdf-image-table-cropper \
  -i paper.pdf \
  -o ./output \
  --type both

Enable OpenDataLab supplementary detection (off by default):

pdf-image-table-cropper \
  -i paper.pdf \
  -o ./output \
  --enable-opendatalab

Enable local daemon mode to reuse loaded models across commands:

pdf-image-table-cropper \
  -i paper.pdf \
  -o ./output \
  --daemon-mode auto \
  --daemon-idle-seconds 300

Increase rendering quality (slower):

pdf-image-table-cropper \
  -i paper.pdf \
  -o ./output \
  --dpi 300

4. CLI Reference

Required:

• -i, --input-pdf: input PDF path
• -o, --output-dir, --storage-root: output root directory (alias)

Core optional arguments:

• --type {both,image,table,code,algorithm} (default: both)
• --pages all|1|1-3|1-3,7,10 (default: all)
• --dpi (default: 200)
• --imgsz: OpenDataLab supplementary input size (default: 1280)
• --conf: OpenDataLab supplementary confidence threshold (default: 0.10)
• --iou: OpenDataLab supplementary IoU threshold (default: 0.45)
• --device cpu|mps|cuda|cuda:0... (default: auto)
• --no-merge: disable connected-components merging (enabled by default)
• --heron-model MODEL_ID: primary docling Heron model (enabled by default)
• --heron-conf: Heron confidence threshold (default: 0.5)
• --enable-opendatalab: enable OpenDataLab YOLO supplement (default: off)
• --metadata-file (default: metadata.json)
• --daemon-mode {off,auto,on} model lifecycle mode (default: off)
• --daemon-socket local Unix socket path (default: /tmp/pdf_cropper_modeld_<uid>.sock)
• --daemon-idle-seconds daemon idle timeout before auto-exit (default: 300)
• --daemon-start-timeout daemon startup wait timeout in seconds (default: 12)
• --daemon-run-timeout: timeout for waiting daemon job response; 0 means no timeout (default: 0)

Model download arguments:

• --model-repo: OpenDataLab supplementary model repo (default: opendatalab/PDF-Extract-Kit-1.0)
• --model-file: OpenDataLab supplementary model file in snapshot (default: models/Layout/YOLO/doclayout_yolo_docstructbench_imgsz1280_2501.pt)
• --hf-cache-dir
• --hf-token

5. Output Layout

output/
└── <pdf_stem>/
    ├── metadata.json
    ├── image/
    ├── table/
    ├── code/
    └── algorithm/

Crop file pattern:

p{page}_{type}_{idx}_{x0}_{y0}_{x1}_{y1}[_merged].jpg

Each crop item in metadata.json includes:

• content_type
• page_index, page_number
• page_size_pdf
• bbox_pdf (PDF coordinates)
• bbox_pixels (pixel coordinates)
• score
• image_path
• merged_from (if merged)

6. Tuning

• Too many misses: lower --conf (e.g. 0.05~0.10)
• Too many false positives: raise --conf (e.g. 0.15~0.30)
• Need finer detail: raise --dpi (commonly 300)
• Too slow or OOM: lower --dpi / --imgsz, or use --device cpu
• Exporting algorithm requires --enable-opendatalab

7. License (Repository Code + Models)

Repository source code uses MIT License.

Model licenses:

• docling-project/docling-layout-heron: Apache-2.0
• opendatalab/PDF-Extract-Kit-1.0: AGPL-3.0(非商用协议, 注意, 按需使用)

8. Documentation Versions

• Chinese: README.md
• English (current): README.en.md

9. SDK Usage

from pdf_cropper import CropJobConfig, crop_pdf, crop_pdf_simple

result = crop_pdf_simple(
  input_pdf="paper.pdf",
  output_dir="./output",
  detect_type="table",
)

config = CropJobConfig(
  input_pdf="paper.pdf",
  output_dir="./output",
  detect_type="both",
  pages="all",
  dpi=200,
  enable_opendatalab=False,
)
result = crop_pdf(config)
print(result["metadata_file"])