数据集:
lewtun/dog_food
任务:
图像分类语言:
en计算机处理:
monolingual大小:
1K<n<10K语言创建人:
found批注创建人:
found源数据集:
original许可:
license:unknownThis is a dataset for multiclass image classification, between 'dog', 'chicken', and 'muffin' classes.
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 ?
TBC
The labels are in English (['dog', 'chicken', 'muffin'])
A sample from the training set is provided below:
{ {'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=300x470 at 0x7F176094EF28>, 'label': 0} }
Train (1875 images) and Test (625 images)
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This dataset was taken from the qw2243c/Image-Recognition-Dogs-Fried-Chicken-or-Blueberry-Muffins? Github repository and randomly splitting 25% of the data for validation.
This data was scraped from the internet and annotated based on the query words.
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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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This dataset was created by @lanceyjt, @yl3829, @wesleytao, @qw2243c and @asyouhaveknown
No information is indicated on the original github repository .
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Thanks to @lewtun for adding this dataset.