docs: introduce docs site (#141)

Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>

docs/examples/export_multimodal.py

@@ -0,0 +1,116 @@
+import datetime
+import logging
+import time
+from pathlib import Path
+
+import pandas as pd
+
+from docling.datamodel.base_models import AssembleOptions, ConversionStatus
+from docling.datamodel.document import DocumentConversionInput
+from docling.document_converter import DocumentConverter
+from docling.utils.export import generate_multimodal_pages
+
+_log = logging.getLogger(__name__)
+
+IMAGE_RESOLUTION_SCALE = 2.0
+
+
+def main():
+    logging.basicConfig(level=logging.INFO)
+
+    input_doc_paths = [
+        Path("./tests/data/2206.01062.pdf"),
+    ]
+    output_dir = Path("./scratch")
+
+    input_files = DocumentConversionInput.from_paths(input_doc_paths)
+
+    # Important: For operating with page images, we must keep them, otherwise the DocumentConverter
+    # will destroy them for cleaning up memory.
+    # This is done by setting AssembleOptions.images_scale, which also defines the scale of images.
+    # scale=1 correspond of a standard 72 DPI image
+    assemble_options = AssembleOptions()
+    assemble_options.images_scale = IMAGE_RESOLUTION_SCALE
+
+    doc_converter = DocumentConverter(assemble_options=assemble_options)
+
+    start_time = time.time()
+
+    converted_docs = doc_converter.convert(input_files)
+
+    success_count = 0
+    failure_count = 0
+    output_dir.mkdir(parents=True, exist_ok=True)
+    for doc in converted_docs:
+        if doc.status != ConversionStatus.SUCCESS:
+            _log.info(f"Document {doc.input.file} failed to convert.")
+            failure_count += 1
+            continue
+
+        rows = []
+        for (
+            content_text,
+            content_md,
+            content_dt,
+            page_cells,
+            page_segments,
+            page,
+        ) in generate_multimodal_pages(doc):
+
+            dpi = page._default_image_scale * 72
+
+            rows.append(
+                {
+                    "document": doc.input.file.name,
+                    "hash": doc.input.document_hash,
+                    "page_hash": page.page_hash,
+                    "image": {
+                        "width": page.image.width,
+                        "height": page.image.height,
+                        "bytes": page.image.tobytes(),
+                    },
+                    "cells": page_cells,
+                    "contents": content_text,
+                    "contents_md": content_md,
+                    "contents_dt": content_dt,
+                    "segments": page_segments,
+                    "extra": {
+                        "page_num": page.page_no + 1,
+                        "width_in_points": page.size.width,
+                        "height_in_points": page.size.height,
+                        "dpi": dpi,
+                    },
+                }
+            )
+        success_count += 1
+
+    # Generate one parquet from all documents
+    df = pd.json_normalize(rows)
+    now = datetime.datetime.now()
+    output_filename = output_dir / f"multimodal_{now:%Y-%m-%d_%H%M%S}.parquet"
+    df.to_parquet(output_filename)
+
+    end_time = time.time() - start_time
+
+    _log.info(f"All documents were converted in {end_time:.2f} seconds.")
+
+    if failure_count > 0:
+        raise RuntimeError(
+            f"The example failed converting {failure_count} on {len(input_doc_paths)}."
+        )
+
+    # This block demonstrates how the file can be opened with the HF datasets library
+    # from datasets import Dataset
+    # from PIL import Image
+    # multimodal_df = pd.read_parquet(output_filename)
+
+    # # Convert pandas DataFrame to Hugging Face Dataset and load bytes into image
+    # dataset = Dataset.from_pandas(multimodal_df)
+    # def transforms(examples):
+    #     examples["image"] = Image.frombytes('RGB', (examples["image.width"], examples["image.height"]), examples["image.bytes"], 'raw')
+    #     return examples
+    # dataset = dataset.map(transforms)
+
+
+if __name__ == "__main__":
+    main()