#### NOTE
This is a **community plugin**, an external project maintained by its respective author.
Community plugins are not part of FiftyOne core and may change independently.
Please review each plugin’s documentation and license before use.
# PDF Loader Plugin
A [FiftyOne plugin](https://docs.voxel51.com/plugins/index.html) for loading
PDFs as images.
## Installation
If you haven’t already,
[install FiftyOne](https://docs.voxel51.com/getting_started/install.html):
```shell
pip install fiftyone
```
Then install the plugin and its dependencies:
```shell
fiftyone plugins download https://github.com/brimoor/pdf-loader
brew install poppler
pip install pdf2image
```
## Usage
### Using the App UI
1. Launch the App:
```py
import fiftyone as fo
dataset = fo.Dataset()
session = fo.launch_app(dataset)
```
1. Press ``` or click the `Browse operations` icon above the grid
2. Run the `pdf_loader` operator
### Using the SDK
You can use the plugin programmatically from Python:
```python
import fiftyone as fo
import fiftyone.operators as foo
import requests
import os
# Download a PDF from a URL (optional - you can use any local PDF)
url = "https://arxiv.org/pdf/2309.11419"
filename = url.split('/')[-1] + ".pdf" # Add .pdf extension
response = requests.get(url)
if response.status_code == 200:
with open(filename, 'wb') as f:
f.write(response.content)
print(f"Downloaded {filename}")
else:
print(f"Failed to download {filename}. Status code: {response.status_code}")
# Load the PDF loader operator
pdf_loader = foo.get_operator("@brimoor/pdf-loader/pdf_loader")
# Create a dataset for the PDF pages
pdf_dataset = fo.Dataset("pdf_dataset")
# Convert PDF to images and add to dataset
pdf_loader(
pdf_dataset,
input_path="./2309.11419.pdf", # Path to your PDF file
output_dir="./pdf_images", # Directory to save the images
dpi=200, # Image quality in DPI
fmt="png", # Image format (png or jpg)
tags=None, # Optional tags for samples
delegate=False # Set to True for async execution
)
```
## What next?
Install the
[PyTesseract OCR](https://github.com/jacobmarks/pytesseract-ocr-plugin) and
[Semantic Document Search](https://github.com/jacobmarks/semantic-document-search-plugin)
plugins to make your documents searchable!
1. Install the plugins and their dependencies:
```shell
fiftyone plugins download https://github.com/jacobmarks/pytesseract-ocr-plugin
pip install pytesseract
```
1. Run the `run_ocr_engine` operator to detect text blocks
2. Run the `create_semantic_document_index` operator to generate a semantic
index for the text blocks
3. Run the `semantically_search_documents` operator to perform arbitrary
searches against the index!
## Implementation
This plugin is a basically a wrapper around the following code:
```py
import os
from pdf2image import convert_from_path
INPUT_PATH = "/path/to/your.pdf"
OUTPUT_DIR = "/path/for/page/images"
os.makedirs(OUTPUT_DIR, exist_ok=True)
convert_from_path(INPUT_PATH, output_folder=OUTPUT_DIR, fmt="jpg")
dataset.add_images_dir(OUTPUT_DIR)
```