Update README.md

README.md

@@ -33,27 +33,32 @@ quebec-traffic-signs/
 │   ├── P-010-fr.png
 │   ├── P-010-en.png
 │   └── ... (all image files)
-├── dataset.csv
+├── metadata.jsonl
 └── README.md
 ```
 
 -   **`images/`**: This directory contains all the image files of the traffic signs. These include both pristine digital assets (SVG/PNG renders) and will be augmented with real-world photos captured under various challenging conditions (e.g., blur, low quality, occlusions, snow, vandalism).
--   **`dataset.csv`**: This CSV file serves as the primary metadata index for the dataset. Each row corresponds to a unique traffic sign image and contains the following fields:
+-   **`metadata.jsonl`**: This JSON Lines file serves as the primary metadata index for the dataset. Each line is a JSON object corresponding to a unique traffic sign image and contains the following fields (aligned with the D1 database schema):
+    -   `image_id`: A unique identifier for the image.
+    -   `file_name`: The relative path to the image file within the `images/` directory (e.g., `images/P-010-fr.png`).
+    -   `source`: Indicates the origin of the image (e.g., `digital_asset`, `real_world_photo`, `synthetic_diffusion`).
     -   `reference_id`: A unique identifier for the sign, often corresponding to official Quebec sign codes (e.g., `P-010-fr`, `P-120-10 (left)`).
-    -   `image`: The relative path to the image file within the `images/` directory (e.g., `images/P-010-fr.png`).
-    -   `explanation`: A short textual explanation or description of the sign's meaning or regulation. (Currently being populated, will include French and English versions in future iterations or a separate `metadata.jsonl`).
-    -   `url`: The original source URL from which the digital asset was downloaded (primarily Wikimedia Commons).
+    -   `explanation_fr`: A detailed explanation of the sign's meaning in French.
+    -   `explanation_en`: A detailed explanation of the sign's meaning in English.
+    -   `real_world_conditions`: A JSON array describing any real-world conditions simulated or observed (e.g., `["snow_occlusion", "blur"]`).
+    -   `is_synthetic`: A boolean indicating if the image is synthetically generated.
+    -   `original_url`: The original source URL from which the digital asset was downloaded (primarily Wikimedia Commons).
 
 ## Data Collection and Annotation
 
-The initial phase of data collection focuses on digital assets sourced from Wikimedia Commons, which provides high-quality SVG renders of official Quebec road signs. These digital assets are processed to extract `reference_id` and `image_url`, and then downloaded locally.
+The initial phase of data collection focuses on digital assets sourced from Wikimedia Commons, which provides high-quality SVG renders of official Quebec road signs. These digital assets are processed to extract `reference_id` and `original_url`, and then downloaded locally.
+
+Annotations, including detailed explanations (French and English) and structured metadata (e.g., `source`, `real_world_conditions`, `is_synthetic`), are compiled into the `metadata.jsonl` file.
 
 Future iterations will incorporate:
 -   **Real-world photos:** Images captured in urban environments (e.g., Montreal) under diverse conditions (varying lighting, weather, angles, partial obstructions, wear and tear, graffiti) to reflect real-world challenges.
 -   **Synthetic data generation:** Leveraging multimodal diffusion models (e.g., Stable Diffusion with ControlNet) to augment the dataset with synthetically generated images that simulate challenging real-world conditions, based on the pristine digital assets. This will significantly increase the dataset's robustness for edge cases.
 
-Annotations are currently derived from the `alt` attributes of image tags and will be enriched with detailed explanations (French and English) and structured metadata (e.g., `source`, `real_world_conditions`, `is_synthetic`) in a `metadata.jsonl` file for more advanced use cases.
-
 ## Usage
 
 This dataset is designed to be easily loaded and used with the Hugging Face `datasets` library.
@@ -65,9 +70,22 @@ from datasets import load_dataset
 dataset = load_dataset("RDLTechworks/quebec-traffic-signs")
 
 # Example of accessing data
-# print(dataset["train"][0]["image"])
-# print(dataset["train"][0]["reference_id"])
-# print(dataset["train"][0]["explanation"])
+# Accessing the first example in the 'train' split
+first_example = dataset["train"][0]
+
+print(f"Image ID: {first_example['image_id']}")
+print(f"Reference ID: {first_example['reference_id']}")
+print(f"French Explanation: {first_example['explanation_fr']}")
+print(f"English Explanation: {first_example['explanation_en']}")
+print(f"Source: {first_example['source']}")
+print(f"Real-world Conditions: {first_example['real_world_conditions']}")
+print(f"Is Synthetic: {first_example['is_synthetic']}")
+print(f"Original URL: {first_example['original_url']}")
+
+# To display the image (requires Pillow installed: pip install Pillow)
+# from PIL import Image
+# image = first_example['image'] # This will be a PIL Image object
+# image.show()
 ```
 
 ## License
@@ -78,4 +96,4 @@ This dataset is intended for research and non-commercial use. The images sourced
 
 For questions or contributions, please contact [your-email@example.com] or visit the [RDLTechworks GitHub repository](https://github.com/RDLTechworks/quebec-traffic-signs) (placeholder).
 
----
+---