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@@ -4,13 +4,16 @@ language: en
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  license: apache-2.0
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  size_categories:
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  - 1K<n<10K
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- task_categories: []
 
 
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  task_ids: []
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  pretty_name: COIL-100
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  tags:
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  - fiftyone
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  - image
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- dataset_summary: '
 
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- This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 7200 samples.
 
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  ## Installation
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- If you haven''t already, install FiftyOne:
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  ```bash
@@ -46,9 +50,9 @@ dataset_summary: '
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  # Load the dataset
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- # Note: other available arguments include ''max_samples'', etc
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- dataset = fouh.load_from_hub("jamarks/COIL-100")
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  # Launch the App
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  session = fo.launch_app(dataset)
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  ```
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-
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- '
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  ---
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  # Dataset Card for COIL-100
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- <!-- Provide a quick summary of the dataset. -->
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-
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-
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-
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  ![image/png](dataset_preview.gif)
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@@ -88,7 +86,7 @@ import fiftyone.utils.huggingface as fouh
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  # Load the dataset
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  # Note: other available arguments include 'max_samples', etc
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- dataset = fouh.load_from_hub("jamarks/COIL-100")
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  # Launch the App
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  session = fo.launch_app(dataset)
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  ### Dataset Description
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- <!-- Provide a longer summary of what this dataset is. -->
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-
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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  - **Language(s) (NLP):** en
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  - **License:** apache-2.0
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@@ -113,116 +108,36 @@ session = fo.launch_app(dataset)
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  <!-- Provide the basic links for the dataset. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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-
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- ## Uses
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-
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- <!-- Address questions around how the dataset is intended to be used. -->
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-
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- ### Direct Use
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-
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- <!-- This section describes suitable use cases for the dataset. -->
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-
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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
 
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- [More Information Needed]
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-
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- ## Dataset Structure
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-
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- <!-- 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. -->
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- [More Information Needed]
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-
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- ## Dataset Creation
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-
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- ### Curation Rationale
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-
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- <!-- Motivation for the creation of this dataset. -->
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- [More Information Needed]
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- ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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  #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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-
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- [More Information Needed]
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- #### Who are the source data producers?
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- <!-- 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. -->
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- [More Information Needed]
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-
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- ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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- #### Annotation process
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- <!-- 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. -->
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- [More Information Needed]
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- #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- [More Information Needed]
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- #### Personal and Sensitive Information
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- <!-- 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. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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-
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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  **BibTeX:**
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- [More Information Needed]
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-
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- **APA:**
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- [More Information Needed]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Dataset Card Authors [optional]
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- [More Information Needed]
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- ## Dataset Card Contact
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- [More Information Needed]
 
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  license: apache-2.0
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  size_categories:
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  - 1K<n<10K
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+ task_categories:
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+ - image-feature-extraction
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+ - image-to-3d
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  task_ids: []
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  pretty_name: COIL-100
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  tags:
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  - fiftyone
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  - image
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+ - clustering
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+ dataset_summary: >
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+ This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 7200
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+ samples.
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  ## Installation
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+ If you haven't already, install FiftyOne:
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  ```bash
 
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  # Load the dataset
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+ # Note: other available arguments include 'max_samples', etc
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+ dataset = fouh.load_from_hub("Voxel51/COIL-100")
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  # Launch the App
 
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  session = fo.launch_app(dataset)
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  ```
 
 
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  ---
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  # Dataset Card for COIL-100
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  ![image/png](dataset_preview.gif)
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  # Load the dataset
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  # Note: other available arguments include 'max_samples', etc
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+ dataset = fouh.load_from_hub("Voxel51/COIL-100")
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  # Launch the App
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  session = fo.launch_app(dataset)
 
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  ### Dataset Description
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+ There are 7,200 images of 100 objects. Each object was turned on a turnable through 360 degrees to vary object pose with respect to a fixed color camera. Images of the objects were taken at pose intervals of 5 degrees. This corresponds to 72 poses per object. There images were then size normalized. Objects have a wide variety of complex geometric and reflectance characteristics.
 
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+ - **Curated by:** Center for Research on Intelligent Systems at the Department of Computer Science , Columbia University
 
 
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  - **Language(s) (NLP):** en
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  - **License:** apache-2.0
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  <!-- Provide the basic links for the dataset. -->
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+ - **Paper:** https://www1.cs.columbia.edu/CAVE/publications/pdfs/Nene_TR96_2.pdf
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+ - **Homepage:** https://www.cs.columbia.edu/CAVE/software/softlib/coil-100.php
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+ ## Uses
 
 
 
 
 
 
 
 
 
 
 
 
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+ This dataset is intended for non-commercial research purposes only.
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  #### Data Collection and Processing
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+ COIL-100 was collected by the Center for Research on Intelligent Systems at the Department of Computer Science , Columbia University. The database contains color images of 100 objects. The objects were placed on a motorized turntable against a black background and images were taken at pose internals of 5 degrees. This dataset was used in a real-time 100 object recognition system whereby a system sensor could identify the object and display its angular pose.
 
 
 
 
 
 
 
 
 
 
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+ ## Citation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  **BibTeX:**
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+ ```bibtex
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+ @article{nene1996columbia,
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+ title={Columbia object image library (coil-100)},
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+ author={Nene, Sameer A and Nayar, Shree K and Murase, Hiroshi},
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+ year={1996},
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+ publisher={Technical report CUCS-006-96}
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+ }
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+ ```
 
 
 
 
 
 
 
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+ ## Dataset Card Authors
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+ [Jacob Marks](https://huggingface.co/jamarks)
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