Update README.md

README.md

@@ -50,7 +50,7 @@ dataset_summary: '
 
   # Note: other available arguments include ''max_samples'', etc
 
-  dataset = fouh.load_from_hub("jamarks/FGVC-Aircraft")
+  dataset = fouh.load_from_hub("Voxel51/FGVC-Aircraft")
 
 
   # Launch the App
@@ -90,7 +90,7 @@ import fiftyone.utils.huggingface as fouh
 
 # Load the dataset
 # Note: other available arguments include 'max_samples', etc
-dataset = fouh.load_from_hub("jamarks/FGVC-Aircraft")
+dataset = fouh.load_from_hub("Voxel51/FGVC-Aircraft")
 
 # Launch the App
 session = fo.launch_app(dataset)
@@ -101,130 +101,79 @@ session = fo.launch_app(dataset)
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
+Fine-Grained Visual Classification of Aircraft (FGVC-Aircraft) is a benchmark dataset for the fine grained visual categorization of aircraft.
 
+**Note** This data has been used as part of the ImageNet FGVC challenge in conjuction with the International Conference on Computer Vision (ICCV) 2013. Test labels were not made available until the challenge due to the ImageNet challenge policy. They have now been released as part of the download above. If you arelady downloaded the iamge archive and want to have access to the test labels, simply download the annotations archive again.
+
+**Note** Images in the benchmark are generously made available for non-commercial research purposes only by a number of airplane spotters. Please note that the original authors retain the copyright of the respective photographs and should be contacted for any other use. For further details see the copyright note below.
 
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Language(s) (NLP):** en
 - **License:** other
 
-### Dataset Sources [optional]
+### Dataset Sources
 
 <!-- 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. -->
-
-[More Information Needed]
+- **Homepage:** https://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/#format
+- **Paper:** [Towards a Detailed Understanding of Objects and Scenes in Natural Images](http://www.clsp.jhu.edu/workshops/archive/ws-12/groups/tduosn/)
 
-### Out-of-Scope Use
-
-<!-- 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
+The dataset contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes. The (main) aircraft in each image is annotated with a tight bounding box and a hierarchical airplane model label.
 
-### Curation Rationale
+Aircraft models are organized in a four-levels hierarchy. The four levels, from finer to coarser, are:
 
-<!-- Motivation for the creation of this dataset. -->
+- **Model**, e.g. *Boeing 737-76J*. Since certain models are nearly visually indistinguishable, this level is not used in the evaluation.
+- **Variant**, e.g. *Boeing 737-700*. A variant collapses all the models that are visually indistinguishable into one class. The dataset comprises 102 different variants.
+- **Family**, e.g. *Boeing 737*. The dataset comprises 70 different families.
+- **Manufacturer**, e.g. *Boeing*. The dataset comprises 41 different manufacturers.
 
-[More Information Needed]
+The data is divided into three equally-sized training, validation and test subsets. The first two sets can be used for development, and the latter should be used for final evaluation only. The format of the data is described next.
 
-### 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?
+## Dataset Creation
 
 <!-- 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]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### 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. -->
+The creation of this dataset started during the Johns Hopkins CLSP Summer Workshop 2012 [Towards a Detailed Understanding of Objects and Scenes in Natural Images](http://www.clsp.jhu.edu/workshops/archive/ws-12/groups/tduosn/) with, in alphabetical order, Matthew B. Blaschko, Ross B. Girshick, Juho Kannala, Iasonas Kokkinos, Siddharth Mahendran, Subhransu Maji, Sammy Mohamed, Esa Rahtu, Naomi Saphra, Karen Simonyan, Ben Taskar, Andrea Vedaldi, and David Weiss.
 
-[More Information Needed]
+The CLSP workshop was supported by the National Science Foundation via Grant No 1005411, the Office of the Director of National Intelligence via the JHU Human Language Technology Center of Excellence; and Google Inc.
 
-#### Who are the annotators?
+A special thanks goes to Pekka Rantalankila for helping with the creation of the airplane hieararchy.
 
-<!-- This section describes the people or systems who created the annotations. -->
+Many thanks to the photographers that kindly made available their images for research purposes. Each photographer is listed below, along with a link to his/her [airlners.net](http://airliners.net/) page:
 
-[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]
+- [Mick Bajcar](http://www.airliners.net/profile/dendrobatid)
+- [Aldo Bidini](http://www.airliners.net/profile/aldobid)
+- [Wim Callaert](http://www.airliners.net/profile/minoeke)
+- [Tommy Desmet](http://www.airliners.net/profile/tommypilot)
+- [Thomas Posch](http://www.airliners.net/profile/snorre)
+- [James Richard Covington](http://www.airliners.net/profile/lemonkitty)
+- [Gerry Stegmeier](http://www.airliners.net/profile/stegi)
+- [Ben Wang](http://www.airliners.net/profile/aal151heavy)
+- [Darren Wilson](http://www.airliners.net/profile/dazbo5)
+- [Konstantin von Wedelstaedt](http://www.airliners.net/profile/fly-k)
+- 
+Please note that the images are made available **exclusively for non-commercial research purposes**. The original authors retain the copyright on the respective pictures and should be contacted for any other usage of them.
 
+## Citation
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
 **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]
+```bibtex
+@techreport{maji13fine-grained,
+   title         = {Fine-Grained Visual Classification of Aircraft},
+   author        = {S. Maji and J. Kannala and E. Rahtu
+                    and M. Blaschko and A. Vedaldi},
+   year          = {2013},
+   archivePrefix = {arXiv},
+   eprint        = {1306.5151},
+   primaryClass  = "cs-cv",
+}
+```
 
-## Dataset Card Contact
+## Dataset Card Author
 
-[More Information Needed]
+[Jacob Marks](https://huggingface.co/jamarks)