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# PODS: Personal Object Discrimination Suite
<h3 align="center"><a href="https://personalized-rep.github.io" style="color: #2088FF;">🌐Project page</a>&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
<a href="https://example2.com" style="color: #2088FF;">📖Paper</a>&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
<a href="#citation" style="color: #2088FF;">GitHub</a><br></h3>

We introduce the PODS (Personal Object Discrimination Suite) dataset, a new benchmark for personalized vision tasks.
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65f9d4100f717eb3e67556df/I6COn1U2CmzZFFs998JsL.jpeg" alt="pods.jpg" />
</p>

## PODS
The PODS dataset is new a benchmark for personalized vision tasks. It includes:
* 100 common household objects from 5 semantic categories
* 4 tasks (classification, retrieval, segmentation, detection)
* 4 test splits with different distribution shifts.
* 12 test images per instance (3 per split).

PODS is [available on HuggingFace](#hf-link-here), or can be directly downloaded [here](#link-here).

Metadata is stored in two files:
* `pods_info.json`:
* `classes`: A list of class names
* `class_to_idx`: Mapping of each class to an integer id
* `class_to_sc`: Mapping of each class to a broad, single-word semantic category
* `class_to_split`: Mapping of each class to the `val` or `test` split.
* `pods_image_annos.json`: Maps every image ID to its class and test split (one of `[train, objects, pose, all]`)

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  download_size: 1168203407
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  dataset_size: 1228220099.0
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  download_size: 1168203407
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  dataset_size: 1228220099.0
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  ---
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+ # PODS: Personal Object Discrimination Suite
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+ <h3 align="center"><a href="https://personalized-rep.github.io" style="color: #2088FF;">🌐Project page</a>&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
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+ <a href="https://example2.com" style="color: #2088FF;">📖Paper</a>&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp
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+ <a href="#citation" style="color: #2088FF;">GitHub</a><br></h3>
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+
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+ We introduce the PODS (Personal Object Discrimination Suite) dataset, a new benchmark for personalized vision tasks.
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+ <p align="center">
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/65f9d4100f717eb3e67556df/I6COn1U2CmzZFFs998JsL.jpeg" alt="pods.jpg" />
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+ </p>
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+
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+ ## PODS
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+ The PODS dataset is new a benchmark for personalized vision tasks. It includes:
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+ * 100 common household objects from 5 semantic categories
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+ * 4 tasks (classification, retrieval, segmentation, detection)
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+ * 4 test splits with different distribution shifts.
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+ * 12 test images per instance (3 per split).
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+
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+ PODS is [available on HuggingFace](#hf-link-here), or can be directly downloaded [here](#link-here).
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+
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+ Metadata is stored in two files:
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+ * `pods_info.json`:
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+ * `classes`: A list of class names
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+ * `class_to_idx`: Mapping of each class to an integer id
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+ * `class_to_sc`: Mapping of each class to a broad, single-word semantic category
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+ * `class_to_split`: Mapping of each class to the `val` or `test` split.
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+ * `pods_image_annos.json`: Maps every image ID to its class and test split (one of `[train, objects, pose, all]`)