Update README.md

README.md

@@ -1,7 +1,54 @@
-# DED Thermal VQA Dataset
+---
+license: cc-by-4.0
+task_categories:
+- visual-question-answering
+language:
+- en
+tags:
+- manufacturing
+- additive-manufacturing
+- directed-energy-deposition
+- ded
+- thermal-imaging
+- vqa
+pretty_name: DED Thermal Visual Question Answering (DD4)
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train.parquet
+  - split: test
+    path: test.parquet
+---
 
-This dataset contains embedded thermal images from laser directed energy deposition.
+# DED-Thermal VQA Dataset (DD4)
 
-Fields: `query`, `image`, `annot`, `reasoning`, `cate`, `task`, `metadata`.
+This dataset is designed for **Visual Question Answering (VQA)** in the domain of advanced manufacturing, specifically focusing on **Directed Energy Deposition (DED)** additive manufacturing processes. It pairs in-situ infra-red (IR) thermal monitoring sequences/images with structured question-answer pairs to facilitate the development of Vision-Language Models (VLMs) capable of understanding physical phenomenon and thermal history in 3D printing.
 
-The source images are 16-bit grayscale TIFF files. The embedded images are normalized JPEG visualizations, while raw intensity statistics are retained in `metadata`.
+---
+
+## Dataset Summary
+
+During the Directed Energy Deposition (DED) process, real-time thermal behavior (e.g., melt pool dynamics, cooling rates, and thermal gradients) is critical to the structural integrity and quality of the final printed components. 
+
+**DD4** dataset provides a benchmark for evaluating multimodal AI agents on their ability to interpret, reason, and answer questions about physical manufacturing dynamics based on thermal visualization data.
+
+* **Task**: Visual Question Answering (VQA)
+* **Domain**: Additive Manufacturing / Directed Energy Deposition (DED)
+* **Modality**: Multi-modal (Thermal Imaging + Natural Language)
+* **Format**: Parquet (compatible with Hugging Face `datasets` library)
+
+---
+
+## Dataset Structure
+
+The directory structure of this dataset is as follows:
+
+```text
+vqa_ded_thermal/
+├── train.parquet          # Training split containing VQA pairs and image features/references
+├── test.parquet           # Testing split for model evaluation
+├── dataset_report.json    # Statistical overview and structural metadata of the dataset
+└── README.md              # Dataset card and documentation