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  ### Dataset Summary
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- This is a dataset for binary image classification, between 'dog' and 'food' classes.
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- The 'dog' class contains images of dogs that look like fried chicken and some that look like images of muffins, and the 'food' class contains images of (you guessed it) fried chicken and muffins ๐Ÿ˜‹
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  ### Supported Tasks and Leaderboards
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  ### Languages
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- The labels are in English (['dog', 'food'])
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  ## Dataset Structure
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  #### Initial Data Collection and Normalization
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- This dataset was taken from the [qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins?](https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-) Github repository, merging the 'chicken' and 'muffin' categories into a single 'food' category, and randomly splitting 10% of the data for validation.
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  ### Annotations
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  ### Discussion of Biases
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- This dataset is imbalanced -- it has more images of food (2000) compared to dogs (1000), due to the original labeling. This should be taken into account when evaluating models.
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  ### Other Known Limitations
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  ### Dataset Summary
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+ This is a dataset for multiclass image classification, between 'dog', 'chicken', and 'muffin' classes.
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+ The 'dog' class contains images of dogs that look like fried chicken and some that look like images of muffins, while the 'chicken' and 'muffin' classes contains images of (you guessed it) fried chicken and muffins ๐Ÿ˜‹
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  ### Supported Tasks and Leaderboards
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  ### Languages
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+ The labels are in English (['dog', 'chicken', 'muffin'])
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  ## Dataset Structure
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  #### Initial Data Collection and Normalization
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+ This dataset was taken from the [qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins?](https://github.com/qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins-) Github repository and randomly splitting 25% of the data for validation.
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  ### Annotations
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  ### Discussion of Biases
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+ This dataset is balanced -- it has an equal number of images of dogs (1000) compared to chicken (1000 and muffin (1000). This should be taken into account when evaluating models.
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  ### Other Known Limitations
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