179 lines
3.5 KiB
Plaintext
179 lines
3.5 KiB
Plaintext
# cv-analysis - Visual (CV-Based) Document Parsing
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parse_pdf()
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This repository implements computer vision based approaches for detecting and parsing visual features such as tables or
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previous redactions in documents.
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## API
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Input message:
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```json
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{
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"targetFilePath": {
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"pdf": "absolute file path",
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"vlp_output": "absolute file path"
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},
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"responseFilePath": "absolute file path",
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"operation": "table_image_inference"
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}
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```
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Response is uploaded to the storage as specified in the `responseFilePath` field. The structure is as follows:
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```json
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{
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...,
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"data": [
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{
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'pageNum': 0,
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'bbox': {
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'x1': 55.3407,
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'y1': 247.0246,
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'x2': 558.5602,
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'y2': 598.0585
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},
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'uuid': '2b10c1a2-393c-4fca-b9e3-0ad5b774ac84',
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'label': 'table',
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'tableLines': [
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{
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'x1': 0,
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'y1': 16,
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'x2': 1399,
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'y2': 16
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},
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...
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],
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'imageInfo': {
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'height': 693,
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'width': 1414
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}
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},
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...
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]
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}
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```
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## Installation
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```bash
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git clone ssh://git@git.iqser.com:2222/rr/cv-analysis.git
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cd cv-analysis
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python -m venv env
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source env/bin/activate
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pip install -e .
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pip install -r requirements.txt
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dvc pull
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```
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## Usage
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### As an API
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The module provided functions for the individual tasks that all return some kind of collection of points, depending on
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the specific task.
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#### Redaction Detection (API)
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The below snippet shows hot to find the outlines of previous redactions.
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```python
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from cv_analysis.redaction_detection import find_redactions
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import pdf2image
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import numpy as np
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pdf_path = ...
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page_index = ...
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page = pdf2image.convert_from_path(pdf_path, first_page=page_index, last_page=page_index)[0]
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page = np.array(page)
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redaction_contours = find_redactions(page)
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```
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## As a CLI Tool
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Core API functionalities can be used through a CLI.
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### Table Parsing
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The tables parsing utility detects and segments tables into individual cells.
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```bash
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python scripts/annotate.py data/test_pdf.pdf 7 --type table
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```
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The below image shows a parsed table, where each table cell has been detected individually.
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### Redaction Detection (CLI)
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The redaction detection utility detects previous redactions in PDFs (filled black rectangles).
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```bash
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python scripts/annotate.py data/test_pdf.pdf 2 --type redaction
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```
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The below image shows the detected redactions with green outlines.
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### Layout Parsing
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The layout parsing utility detects elements such as paragraphs, tables and figures.
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```bash
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python scripts/annotate.py data/test_pdf.pdf 7 --type layout
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```
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The below image shows the detected layout elements on a page.
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### Figure Detection
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The figure detection utility detects figures specifically, which can be missed by the generic layout parsing utility.
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```bash
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python scripts/annotate.py data/test_pdf.pdf 3 --type figure
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```
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The below image shows the detected figure on a page.
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## Running as a service
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### Building
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Build base image
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```bash
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bash setup/docker.sh
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```
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Build head image
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```bash
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docker build -f Dockerfile -t cv-analysis . --build-arg BASE_ROOT=""
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```
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### Usage (service)
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Shell 1
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```bash
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docker run --rm --net=host --rm cv-analysis
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```
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Shell 2
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```bash
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python scripts/client_mock.py --pdf_path /path/to/a/pdf
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```
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