mrdbourke/learn_hf_food_not_food_image_captions

--- dataset_info: features: - name: text dtype: string - name: label dtype: string splits: - name: train num_bytes: 20253 num_examples: 250 download_size: 11945 dataset_size: 20253 configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 --- # Food/Not Food Image Caption Dataset Small dataset of synthetic food and not food image captions. Text generated using Mistral Chat/Mixtral. Can be used to train a text classifier on food/not_food image captions as a demo before scaling up to a larger dataset. See [Colab notebook](https://colab.research.google.com/drive/14xr3KN_HINY5LjV0s2E-4i7v0o_XI3U8?usp=sharing) on how dataset was created. ## Example usage ```python import random from datasets import load_dataset # Load dataset loaded_dataset = load_dataset("mrdbourke/learn_hf_food_not_food_image_captions") # Get random index rand_idx = random.randint(0, len(loaded_dataset["train"])) # All samples are in the 'train' split by default (unless otherwise stated) random_sample = loaded_dataset["train"][rand_idx] print(f"Showing sample: {rand_idx}\n{random_sample}") ``` ``` >>> Showing sample: 71 {'text': 'A kabob of grilled vegetables, including zucchini, squash, and onion, perfect for a summer barbecue.', 'label': 'food'} ```

原始信息汇总

Food/Not Food Image Caption Dataset

数据集概述

• 数据集名称: Food/Not Food Image Caption Dataset
• 数据集描述: 这是一个合成食物和非食物图像标题的小型数据集。
• 用途: 可用于训练文本分类器，识别食物/非食物图像标题，作为在扩展到更大数据集之前的演示。

数据集结构

• 特征:
  • text: 字符串类型，表示图像标题。
  • label: 字符串类型，表示标签（食物或非食物）。
• 分割:
  • train: 训练集，包含250个样本，总大小为20253字节。

数据集大小

• 下载大小: 11945字节
• 数据集大小: 20253字节

许可证

• 许可证: Apache 2.0