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image
imagewidth (px)
4.08k
4.16k
label
class label
6 classes
0Arts
0Arts
0Arts
0Arts
0Arts
1Football
1Football
1Football
1Football
1Football
2Gates Center
2Gates Center
2Gates Center
2Gates Center
2Gates Center
3Hamerschlag
3Hamerschlag
3Hamerschlag
3Hamerschlag
3Hamerschlag
4Scaife
4Scaife
4Scaife
4Scaife
4Scaife
4Scaife
5Staircase to the Sky
5Staircase to the Sky
5Staircase to the Sky
5Staircase to the Sky
5Staircase to the Sky
5Staircase to the Sky

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This dataset covers 32 original photos of 6 landmarks at Carnegie Mellon University along with 320 pieces of artifial data. This could be used for image identification tasks or geolocation tasks.

Dataset Details

Dataset Sources [optional]

  • Repository: {{ repo | default("[More Information Needed]", true)}}

Uses

The main use was to train tabular machine learning models to predict what landmark is being shown or to predict the GPS location of a landmark in an image.

Direct Use

The direct use would be location or geolocal positioning tasks.

Out-of-Scope Use

Dataset Structure

This dataset consists of two splits An original split with 32 photos An artificial split with 320 photos

The tasks fall into 6 categories based on the building pictured

  1. Arts Building
  2. Football Stadium
  3. Gates Center
  4. Hamerschlag Hall
  5. Scaife Hall
  6. Staircase to the Sky

Dataset Creation

Source Data

Source data is photos from a Moto 5G around CMU campus

Data Collection and Processing

Data for this was collected by the owner using a personal phone

Who are the source data producers?

Data was initially produced by the owner.

Bias, Risks, and Limitations

This is a very small data set and will likely have issues with training and fitting, especially for more complex identification problems.

Recommendations

This dataset probably has limited accuracy as a first draft but may be useful for learning how to train models.

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