Update README.md

Filling in README

README.md

@@ -14,7 +14,8 @@ tags:
 - image
 - image-classification
 - image-segmentation
-dataset_summary: '
+- anomaly-detection
+dataset_summary: >
 
 
 
@@ -22,13 +23,14 @@ dataset_summary: '
 
 
 
-  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 5354 samples.
+  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 5354
+  samples.
 
 
   ## Installation
 
 
-  If you haven''t already, install FiftyOne:
+  If you haven't already, install FiftyOne:
 
 
   ```bash
@@ -50,9 +52,9 @@ dataset_summary: '
 
   # Load the dataset
 
-  # Note: other available arguments include ''max_samples'', etc
+  # Note: other available arguments include 'max_samples', etc
 
-  dataset = fouh.load_from_hub("jamarks/mvtec-ad")
+  dataset = fouh.load_from_hub("Voxel51/mvtec-ad")
 
 
   # Launch the App
@@ -60,8 +62,6 @@ dataset_summary: '
   session = fo.launch_app(dataset)
 
   ```
-
-  '
 ---
 
 # Dataset Card for MVTec AD
@@ -92,7 +92,7 @@ import fiftyone.utils.huggingface as fouh
 
 # Load the dataset
 # Note: other available arguments include 'max_samples', etc
-dataset = fouh.load_from_hub("jamarks/mvtec-ad")
+dataset = fouh.load_from_hub("Voxel51/mvtec-ad")
 
 # Launch the App
 session = fo.launch_app(dataset)
@@ -103,130 +103,65 @@ session = fo.launch_app(dataset)
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
-
+MVTec AD is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. It contains over 5000 high-resolution images divided into fifteen different object and texture categories. Each category comprises a set of defect-free training images and a test set of images with various kinds of defects as well as images without defects.
 
+Pixel-precise annotations of all anomalies are also provided.
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** en
-- **License:** cc-by-4.0
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
+The data is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+In particular, it is not allowed to use the dataset for commercial purposes. If you are unsure whether or not your application violates the non-commercial use clause of the license, please contact the dataset's authors.
 
-## Uses
+If you have any questions or comments about the dataset, feel free to contact the dataset's authors via email at re-request@mvtec.com
 
-<!-- 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. -->
+- **Language(s) (NLP):** en
+- **License:** cc-by-4.0
 
-[More Information Needed]
+### Dataset Sources
 
-## Dataset Structure
+<!-- Provide the basic links for the dataset. -->
 
-<!-- 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. -->
+- **Dataset Homepage** https://www.mvtec.com/company/research/datasets/mvtec-ad 
+- **Paper:** [The MVTec Anomaly Detection Dataset: A Comprehensive Real-World
+Dataset for Unsupervised Anomaly Detection](https://link.springer.com/content/pdf/10.1007/s11263-020-01400-4.pdf)
 
-[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]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
+Data downloaded and converted from [MVTec website](https://www.mvtec.com/company/research/datasets/mvtec-ad)
 
-<!-- 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]
+## 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
+
+@article{Bergmann2021MVTecAnomalyDetection,
+  title={The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection},
+  author={Bergmann, Paul and Batzner, Kilian and Fauser, Michael and Sattlegger, David and Steger, Carsten},
+  journal={International Journal of Computer Vision},
+  volume={129},
+  number={4},
+  pages={1038--1059},
+  year={2021},
+  doi={10.1007/s11263-020-01400-4}
+}
+
+@inproceedings{Bergmann2019MVTecAD,
+  title={MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection},
+  author={Bergmann, Paul and Fauser, Michael and Sattlegger, David and Steger, Carsten},
+  booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  pages={9584--9592},
+  year={2019},
+  doi={10.1109/CVPR.2019.00982}
+}
+```
 
-## Dataset Card Contact
+## Dataset Card Authors
 
-[More Information Needed]
+[Jacob Marks](https://huggingface.co/jamarks)