Update README.md

README.md

@@ -16,4 +16,75 @@ tags:
 pretty_name: 'Better Than Real: Synthetic Apple Detection for Orchards'
 size_categories:
 - 1K<n<10K
----
+---
+
+
+# 🍎 ApplesM5-Dataset
+
+This dataset contains annotated object detection data used in the **Synetic AI Apple Benchmark** study, measuring the effectiveness of rendered (synthetic) data versus real-world data for training small vision models. The dataset was constructed using photorealistic, physics-accurate 3D renders of apples in orchard scenes, with perfect annotations and environmental diversity.
+
+This dataset supports object detection models such as YOLOv8 and RT-DETR, and includes:
+
+- RGB images
+- Bounding box annotations (COCO format)
+- Real and rendered training/validation splits
+- Metadata for benchmark reproduction
+
+## 📊 Use Cases
+
+- Object detection
+- Real vs synthetic data performance evaluation
+- Model training and validation
+- Benchmarking data efficiency in agriculture
+
+## 📁 Dataset Structure
+ApplesM5-Dataset/
+├── images/
+│   ├── train/
+│   ├── val/
+├── annotations/
+│   ├── instances_train.json
+│   ├── instances_val.json
+├── metadata/
+│   ├── image_metadata.csv
+
+## 🔬 Benchmark Context
+
+This dataset was used in the Synetic AI whitepaper to compare multiple training strategies:
+- Real-only
+- Rendered-only
+- Rendered + real validation
+- Joint (rendered + real) training
+
+Rendered data outperformed real data by up to **34% mAP** in certain configurations, especially at low confidence thresholds where operational reliability matters most.
+
+## 📄 Citation & Whitepaper
+
+🔗 Whitepaper coming soon. Visit [synetic.ai](https://synetic.ai) for updates.
+
+Once published, this section will include the official citation and DOI link.
+
+## 🔧 License
+
+MIT License
+
+## 🔤 Language
+
+No language data. This dataset is image-based.
+
+## 🏷️ Tags
+
+`synthetic-data`, `object-detection`, `agriculture`, `benchmark`, `rendered`, `real-vs-synthetic`
+
+## 🎯 Task Categories
+
+- Object Detection
+
+## 📦 Size Category
+
+10K < # images < 100K
+
+---
+
+**Contact**: For questions or commercial licensing, please visit [synetic.ai](https://synetic.ai).
+