Related Objects of Interest: egg, chicken, garlic, ingredients, milk, * 50% probability of horizontal flip, * auto-orientation of pixel data (with exif-orientation stripping), * equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, * random rotation of between -15 and +15 degrees, * randomly crop between 0 and 20 percent of the image
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Top Ingredient Datasets and Models
The datasets below can be used to train fine-tuned models for ingredient detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the ingredient datasets below.
215 images 10 classes
131 images 7 classes
100 images 34 classes
881 images 5241 classes
camera cheese coconut juice line nose salad " "30 "กวดขันวินัยจราจร" "ถ้ามีของครบแม่ครัวจัดให้เลยค่ะ" "ทางร้านเรามี" "ท้องถิ่นดี ภาษีช่วย ท้องถื่นสวย ภาษีสร้าง" "ยินดีรับบัตรเกษตรสุขใจ "ลิ้มจี่จักรพรรดิ์" "สะพานลอยชีวิต" "เครื่องดื่ม อร่อย สด ชื่น ชื่นใจ ใครๆก็ชอบ--ต้องลอง!" "เชฟเลือก--- "เหนือกว่าอร่อยคือ "ไซเลี่ยม ฮัสท์"
3006 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) 13 14 15 16 17 18 19 20 21 22 23 24 25 26
by ingredients
9335 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 23 24 25 26 27 28 29 30
3006 images 38 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise * Random rotation of between -15 and +15 degrees * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 23 24 25 26 27 28 29 30
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