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---
license: mit
language:
- en
pretty_name: HW1 Image Dataset
---
# Dataset Card for {{ pretty_name | default("Dataset Name", true) }}
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 Description
- **Curated by:** Carnegie Mellon University: 24-679
- **Shared by [optional]:** Devin DeCosmo
- **Language(s) (NLP):** English
- **License:** MIT
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **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. |