Update README.md

README.md

@@ -13,9 +13,6 @@ tags:
 - object-detection
 dataset_summary: '
 
-
-
-
   This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 35000 samples.
 
 
@@ -46,7 +43,7 @@ dataset_summary: '
 
   # Note: other available arguments include ''max_samples'', etc
 
-  dataset = fouh.load_from_hub("harpreetsahota/GQA-Scene-Graph")
+  dataset = fouh.load_from_hub("Voxel51/GQA-Scene-Graph")
 
 
   # Launch the App
@@ -60,14 +57,14 @@ dataset_summary: '
 
 # Dataset Card for GQA-35k
 
-<!-- Provide a quick summary of the dataset. -->
-
-
-
+![image](gqa.png)
 
+The GQA (Visual Reasoning in the Real World) dataset is a large-scale visual question answering dataset that includes scene graph annotations for each image.
 
 This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 35000 samples.
 
+Note: This dataset does not contain questions, only the scene graph annotations as detection-level attributes.
+
 ## Installation
 
 If you haven't already, install FiftyOne:
@@ -84,141 +81,76 @@ import fiftyone.utils.huggingface as fouh
 
 # Load the dataset
 # Note: other available arguments include 'max_samples', etc
-dataset = fouh.load_from_hub("harpreetsahota/GQA-Scene-Graph")
+dataset = fouh.load_from_hub("Voxel51/GQA-Scene-Graph")
 
 # Launch the App
 session = fo.launch_app(dataset)
 ```
 
-
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
 
+## Scene Graph Annotations
 
+- Each of the 113K images in GQA is associated with a detailed scene graph describing the objects, attributes and relations present.
+- 
+- The scene graphs are based on a cleaner version of the Visual Genome scene graphs.
+- 
+- For each image, the scene graph is provided as a dictionary (sceneGraph) containing:
+  - Image metadata like width, height, location, weather
+  - A dictionary (objects) mapping each object ID to its name, bounding box coordinates, attributes, and relations[6]
+  - Relations are represented as triples specifying the predicate (e.g. "holding", "on", "left of") and the target object ID[6]
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
+- **Curated by:** Drew Hudson & Christopher Manning
+- **Shared by:** [Harpreet Sahota](https://x.com/datascienceharp), Hacker-in-Residence at Voxel51
 - **Language(s) (NLP):** en
-- **License:** [More Information Needed]
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the dataset is intended to be used. -->
-
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
+- **License:** 
+- GQA annotations (scene graphs, questions, programs) licensed under CC BY 4.0
+- Images sourced from Visual Genome may have different licensing terms
 
-[More Information Needed]
+### Dataset Sources
 
-### Out-of-Scope Use
+- **Repository:** https://cs.stanford.edu/people/dorarad/gqa/
+- **Paper :** https://arxiv.org/pdf/1902.09506
+- **Demo:** https://cs.stanford.edu/people/dorarad/gqa/vis.html
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
+Here's the information presented as a markdown table:
 
-### Annotations [optional]
+| Field | Type | Description |
+|-------|------|-------------|
+| location | str | Optional. The location of the image, e.g. kitchen, beach. |
+| weather | str | Optional. The weather in the image, e.g. sunny, cloudy. |
+| objects | dict | A dictionary from objectId to its object. |
+| &nbsp;&nbsp;&nbsp;&nbsp;object | dict | A visual element in the image (node). |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;name | str | The name of the object, e.g. person, apple or sky. |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;x | int | Horizontal position of the object bounding box (top left). |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;y | int | Vertical position of the object bounding box (top left). |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;w | int | The object bounding box width in pixels. |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;h | int | The object bounding box height in pixels. |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;attributes | [str] | A list of all the attributes of the object, e.g. blue, small, running. |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;relations | [dict] | A list of all outgoing relations (edges) from the object (source). |
+| &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;relation | dict | A triple representing the relation between source and target objects. |
 
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+Note: I've used non-breaking spaces (`&nbsp;`) to indent the nested fields in the 'Field' column to represent the hierarchy. This helps to visually distinguish the nested structure within the table.
 
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+## Citation
 
 **BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
-
-## Dataset Card Contact
-
-[More Information Needed]
+```bibtex
+@article{Hudson_2019,
+   title={GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering},
+   ISBN={9781728132938},
+   url={http://dx.doi.org/10.1109/CVPR.2019.00686},
+   DOI={10.1109/cvpr.2019.00686},
+   journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+   publisher={IEEE},
+   author={Hudson, Drew A. and Manning, Christopher D.},
+   year={2019},
+   month={Jun}
+}
+```