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Pet dataset has 37 classes roughly 200 images for each class. The images have a large variations in scale, pose and lighting.

Overview We have created a 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. Downloads The data needed for evaluation are: Dataset Groundtruth data

The Oxford-IIIT pet dataset is a 37 category pet image dataset with roughly 200 images for each class. The images have large variations in scale ...

120 dog breeds; ~150 images per class; Total images: 20,580. Download dataset · Affenpinscher (150 images) ImageNet synset: n02110627 · Afghan ...

Jun 14, 2019 · The Oxford-IIIT Pet Dataset is a 37 category pet dataset with roughly 100 images for each class created by the Visual Geometry Group at Oxford. The images have large variations in scale, pose and lighting. All images have an associated ground truth annotation of the breed, head ROI, and pixel level trimap segmentation. Inspiration

Jan 29, 2019 · The Oxford-IIIT Pet Dataset is a 37 category pet dataset with roughly 200 images for each class created by the Visual Geometry Group at Oxford. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. Annotation Examples

PET-MR Dataset. Simultaneously acquired positron emission tomography and magnetic resonance data of the brain, plus joint image reconstruction code.

The Oxford-IIIT Pet Dataset has 37 categories with roughly 200 images for each class. The images have a large variations in scale, pose and lighting.

PET Image Data RAW, PRE- AND POST-PROCESSED IMAGE FILES, PIB (ADNI1), FDG (ADNI1/GO/2), FLORBETAPIR (ADNI GO/2/3), FLORBETABEN (ADNI3), and TAU IMAGING (ADNI3) The collection of these images is central to meeting ADNI’s objective of developing biomarkers to track both the progression of Alzheimer’s disease and changes in the underlying pathology.

The Oxford Pets dataset (also known as the "dogs vs cats" dataset) is a collection of images and annotations labeling various breeds of dogs and cats.

PET Image Data RAW, PRE- AND POST-PROCESSED IMAGE FILES, PIB (ADNI1), FDG (ADNI1/GO/2), FLORBETAPIR (ADNI GO/2/3), FLORBETABEN (ADNI3), and TAU IMAGING (ADNI3) The collection of these images is central to meeting ADNI’s objective of developing biomarkers to track both the progression of Alzheimer’s disease and changes in the underlying pathology.

We have created a 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. Downloads The data needed for evaluation are: Dataset Groundtruth data

The collection of these images is central to meeting ADNI's objective of developing biomarkers to track both the progression of Alzheimer's disease and changes ...

We have created a 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting.

Animal Image Dataset (DOG, CAT and PANDA) | Kaggle. Ashish Saxena · Updated 3 years ago.

Animal Image Dataset(DOG, CAT and PANDA) Dataset for Image Classification Practice. Animal Image Dataset(DOG, CAT and PANDA) Data. Code (23) Discussion (0) Metadata. About Dataset. No description available. Animals. Edit Tags. close. search. Apply up to 5 tags to help Kaggle users find your dataset. Animals close. Apply. Usability.

Animal Image Dataset(DOG, CAT and PANDA) · 38656 · 9597 · 0.25 · 21 · 23 · 24 · 3.13.