Update README.md

README.md

@@ -46,7 +46,7 @@ dataset_summary: '
 
   # Note: other available arguments include ''max_samples'', etc
 
-  dataset = fouh.load_from_hub("harpreetsahota/StreetViewHouseNumbers")
+  dataset = fouh.load_from_hub("Voxel51/StreetViewHouseNumbers")
 
 
   # Launch the App
@@ -60,10 +60,15 @@ dataset_summary: '
 
 # Dataset Card for Street View House Numbers
 
-<!-- Provide a quick summary of the dataset. -->
+![image](SVHN.gif)
 
+The Street View House Numbers (SVHN) dataset is a large real-world image dataset used for developing machine learning and object recognition algorithms. It contains over 600,000 labeled images of house numbers taken from Google Street View.
 
+The images are cropped to a fixed resolution of 32x32 pixels, centered around a single character but may contain some distractors at the sides.
 
+SVHN is similar to the MNIST dataset but incorporates significantly more labeled data and comes from a harder, unsolved, real-world problem of recognizing digits and numbers in natural scene images. 
+
+The dataset here is provided as original images with character level bounding boxes
 
 
 This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 33402 samples.
@@ -93,132 +98,29 @@ session = fo.launch_app(dataset)
 
 ## Dataset Details
 
-### Dataset Description
-
-<!-- Provide a longer summary of what this dataset is. -->
-
-
-
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
+- **Curated by:** Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, Andrew Y. Ng
+- **Funded by [optional]:** Google Inc., Stanford University
 - **Shared by [optional]:** [More Information Needed]
-- **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. -->
-
-[More Information Needed]
-
-### 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
-
-### 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?
+- **License:** non-commercial use only
 
-<!-- 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. -->
+For questions regarding the dataset, please contact streetviewhousenumbers@gmail.com
 
-[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. -->
-
-[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. -->
+### Dataset Sources [optional]
 
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+- **Repository:** http://ufldl.stanford.edu/housenumbers
+- **Paper [optional]:** http://ufldl.stanford.edu/housenumbers/nips2011_housenumbers.pdf
 
 ## 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. -->
-
 **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
+@inproceedings{netzer2011reading,
+  title={Reading digits in natural images with unsupervised feature learning},
+  author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
+  booktitle={NIPS workshop on deep learning and unsupervised feature learning},
+  volume={2011},
+  number={2},
+  pages={5},
+  year={2011}
+}
+```