Update README.md

README.md

@@ -1,8 +1,7 @@
 ---
-license: mit
-task_categories:
-- image-classification
-pretty_name: Food-100 Data Set
+license: unknown
+paperswithcode_id: food-101
+pretty_name: Food-101 Data Set
 size_categories:
 - 100K<n<1M
 tags:
@@ -13,24 +12,77 @@ tags:
 - enhanced
 language:
 - en
+source_datasets:
+- extended|other-foodspotting
+- extended|food101
+task_categories:
+- image-classification
+task_ids:
+- multi-class-image-classification
 ---
 # Dataset Card for Food-101-Enriched (Enhanced by Renumics)
 
 ## Dataset Description
 
-- **Homepage:** [Renumics Homepage](https://renumics.com/)
+- **Homepage:** [Renumics Homepage](https://renumics.com/?hf-dataset-card=food101-enriched)
 - **GitHub** [Spotlight](https://github.com/Renumics/spotlight)
 - **Dataset Homepage** [data.vision.ee.ethz.ch](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/)
 - **Paper:** [Food-101 – Mining Discriminative Components with Random Forests](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/static/bossard_eccv14_food-101.pdf)
 
 ### Dataset Summary
 
+[Data-centric AI](https://datacentricai.org) principles have become increasingly important for real-world use cases. At [Renumics](https://renumics.com/?hf-dataset-card=food101-enriched) we believe that classical benchmark datasets and competitions should be extended to reflect this development. 
+
+This is why we are publishing benchmark datasets with application-specific enrichments (e.g. embeddings, baseline results, uncertainties, label error scores). We hope this helps the ML community in the following ways:
+1. Enable new researchers to quickly develop a profound understanding of the dataset.
+2. Popularize data-centric AI principles and tooling in the ML community.
+3. Encourage the sharing of meaningful qualitative insights in addition to traditional quantitative metrics.
+
+This dataset is an enriched version of the [Food101 Data Set](https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/).
+
+### Explore the Dataset
+
+![Analyze Food101 with Spotlight](https://spotlight.renumics.com/resources/hf-food101-enriched.png)
+
+The enrichments allow you to quickly gain insights into the dataset. The open source data curation tool [Renumics Spotlight](https://github.com/Renumics/spotlight) enables that with just a few lines of code:
+
+Install datasets and Spotlight via [pip](https://packaging.python.org/en/latest/key_projects/#pip):
+
+```python
+!pip install renumics-spotlight datasets
+```
+
+Load the dataset from huggingface in your notebook:
+
+```python
+import datasets
+
+dataset = datasets.load_dataset("renumics/food101-enriched", split="train")
+```
+
+Start exploring with a simple:
+
+```python
+from renumics import spotlight
+
+df = dataset.to_pandas()
+spotlight.show(df_show, port=8000, dtype={"image": spotlight.Image})
+```
+You can use the UI to interactively configure the view on the data. Depending on the concrete tasks (e.g. model comparison, debugging, outlier detection) you might want to leverage different enrichments and metadata.
+
+
+### Food101 Dataset
+
 This data set contains 101'000 images from 101 food categories.
 For each class, 250 manually reviewed test images are provided as well as 750 training images. 
 On purpose, the training images were not cleaned, and thus still contain some amount of noise. 
 This comes mostly in the form of intense colors and sometimes wrong labels. 
 All images were rescaled to have a maximum side length of 512 pixels.
 
+### Supported Tasks and Leaderboards
+
+- `image-classification`: The goal of this task is to classify a given image of a dish into one of 101 classes. The leaderboard is available [here](https://paperswithcode.com/sota/fine-grained-image-classification-on-food-101).
+
 ### Languages
 
 English class labels.
@@ -39,9 +91,9 @@ English class labels.
 
 ### Data Instances
 
-Sample data instance:
+A sample from the training set is provided below:
 
-```
+```python
 {
   "image": "/huggingface/datasets/downloads/extracted/49750366cbaf225ce1b5a5c033fa85ceddeee2e82f1d6e0365e8287859b4c7c8/0/0.jpg",
   "label": 6,
@@ -49,6 +101,115 @@ Sample data instance:
   "split": "train"
 }
 ```
+<details>
+  <summary>Class Label Mappings</summary>
+
+  ```json
+  {
+    "apple_pie": 0,
+    "baby_back_ribs": 1,
+    "baklava": 2,
+    "beef_carpaccio": 3,
+    "beef_tartare": 4,
+    "beet_salad": 5,
+    "beignets": 6,
+    "bibimbap": 7,
+    "bread_pudding": 8,
+    "breakfast_burrito": 9,
+    "bruschetta": 10,
+    "caesar_salad": 11,
+    "cannoli": 12,
+    "caprese_salad": 13,
+    "carrot_cake": 14,
+    "ceviche": 15,
+    "cheesecake": 16,
+    "cheese_plate": 17,
+    "chicken_curry": 18,
+    "chicken_quesadilla": 19,
+    "chicken_wings": 20,
+    "chocolate_cake": 21,
+    "chocolate_mousse": 22,
+    "churros": 23,
+    "clam_chowder": 24,
+    "club_sandwich": 25,
+    "crab_cakes": 26,
+    "creme_brulee": 27,
+    "croque_madame": 28,
+    "cup_cakes": 29,
+    "deviled_eggs": 30,
+    "donuts": 31,
+    "dumplings": 32,
+    "edamame": 33,
+    "eggs_benedict": 34,
+    "escargots": 35,
+    "falafel": 36,
+    "filet_mignon": 37,
+    "fish_and_chips": 38,
+    "foie_gras": 39,
+    "french_fries": 40,
+    "french_onion_soup": 41,
+    "french_toast": 42,
+    "fried_calamari": 43,
+    "fried_rice": 44,
+    "frozen_yogurt": 45,
+    "garlic_bread": 46,
+    "gnocchi": 47,
+    "greek_salad": 48,
+    "grilled_cheese_sandwich": 49,
+    "grilled_salmon": 50,
+    "guacamole": 51,
+    "gyoza": 52,
+    "hamburger": 53,
+    "hot_and_sour_soup": 54,
+    "hot_dog": 55,
+    "huevos_rancheros": 56,
+    "hummus": 57,
+    "ice_cream": 58,
+    "lasagna": 59,
+    "lobster_bisque": 60,
+    "lobster_roll_sandwich": 61,
+    "macaroni_and_cheese": 62,
+    "macarons": 63,
+    "miso_soup": 64,
+    "mussels": 65,
+    "nachos": 66,
+    "omelette": 67,
+    "onion_rings": 68,
+    "oysters": 69,
+    "pad_thai": 70,
+    "paella": 71,
+    "pancakes": 72,
+    "panna_cotta": 73,
+    "peking_duck": 74,
+    "pho": 75,
+    "pizza": 76,
+    "pork_chop": 77,
+    "poutine": 78,
+    "prime_rib": 79,
+    "pulled_pork_sandwich": 80,
+    "ramen": 81,
+    "ravioli": 82,
+    "red_velvet_cake": 83,
+    "risotto": 84,
+    "samosa": 85,
+    "sashimi": 86,
+    "scallops": 87,
+    "seaweed_salad": 88,
+    "shrimp_and_grits": 89,
+    "spaghetti_bolognese": 90,
+    "spaghetti_carbonara": 91,
+    "spring_rolls": 92,
+    "steak": 93,
+    "strawberry_shortcake": 94,
+    "sushi": 95,
+    "tacos": 96,
+    "takoyaki": 97,
+    "tiramisu": 98,
+    "tuna_tartare": 99,
+    "waffles": 100
+  }
+  ```
+</details>
 
 ### Data Fields