Update README.md

README.md

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 license: cc-by-nc-sa-4.0
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+# DocQT - Improving Document Forgery Localization Robustness via Diverse JPEG Quantization-Tables
+
+Repository containing JPEG quantization tables used for the Real-QT protocol.
+Dataset name: DocQT.
+Only header-extracted quantization matrices are provided.
+
+## Available quantization tables
+
+- Luminance tables: `quantification_luminance.json`
+	- Number of tables: 859
+- Chrominance tables: `quantification_chrominance.json`
+	- Number of tables: 294
+
+## File format
+
+Both files are stored in JSON for better portability and long-term compatibility.
+
+- Root object: a list of quantization tables
+- One table: a flat list of 64 integers
+- Table values: integers
+
+In other words, each file follows this structure:
+
+- list[table]
+- table = list[64 integer values]
+
+## Example: use quantization tables with Pillow JPEG compression
+
+```python
+import json
+from pathlib import Path
+from PIL import Image
+
+
+def load_quantization_tables(base_dir: str = ".") -> tuple[list, list]:
+	base_path = Path(base_dir)
+
+	luminance_tables = json.loads(
+		(base_path / "quantification_luminance.json").read_text(encoding="utf-8")
+	)
+	chrominance_tables = json.loads(
+		(base_path / "quantification_chrominance.json").read_text(encoding="utf-8")
+	)
+
+	return luminance_tables, chrominance_tables
+
+luminance_tables, chrominance_tables = load_quantization_tables(".")
+
+# Choose the table indices you want to use for compression.
+luma_idx = 0
+chroma_idx = 0
+
+luma_qtable = luminance_tables[luma_idx]
+chroma_qtable = chrominance_tables[chroma_idx]
+
+with Image.open("input.png") as image:
+	image = image.convert("RGB")
+	image.save(
+		"output_custom_qtables.jpg",
+		format="JPEG",
+		qtables=[luma_qtable, chroma_qtable],
+		subsampling="4:2:0",
+		optimize=True,
+	)
+
+# Note: avoid passing a quality value if you want to keep your custom qtables as-is.
+```