datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
nano-banana-pro-prompts-datasets
🖼️ Nano Banana Pro Prompt Dataset
🖼️ The ultimate Nano Banana Pro prompt dataset (6GB+). 26,000+ image generation prompts with full metadata and preview images. Truly open source: No login, no ads, no redirection. Just pure data for AI image creators.
This project is a massive collection of prompts used for Nano Banana Pro AI image model and the resulting generated images. The entire dataset exceeds 6GB and contains 26,000+ images, all structured into a comprehensive… See the full description on the dataset page: https://huggingface.co/datasets/Goku-OpenLab/nano-banana-pro-prompts-datasets.open-vision-banana-snvc-train-full
SNVC-50M v5_full — Multi-Task Vision Dataset
Description
This dataset is a curated subset of the SenseNova Vision Corpus 50M (SNVC-50M), containing 43,509 samples across 6 vision task families and 31 source datasets. Each sample follows a conversational format with interleaved <image> tokens, designed for training vision-language models (VLMs).
Coverage: 43,509 / 57,878 (75.2%) of the original sampling plan. 23 datasets at 100%, 8 partial, 12 unrecoverable… See the full description on the dataset page: https://huggingface.co/datasets/gatilin/open-vision-banana-snvc-train-full.banana-vidorev3-fullpipe
Banana ViDoRe v3 Fullpipe
Nano Banana Pro full-pipeline synthetic training data for ViDoRe v3 finance and industrial domains.
This repository contains 4670 training records and 40190 unique referenced images across
domain-separated ColFlor/ColQwen training splits. Images are included in the repository and paths in each JSONL are
relative to that domain directory.
Generated at: 2026-06-29T09:39:01.644860+00:00
Layout
finance/train.jsonl
finance/metadata.json… See the full description on the dataset page: https://huggingface.co/datasets/vkehfdl1/banana-vidorev3-fullpipe.banana-vidorev3-synthetic-arms
Banana ViDoRe v3 Synthetic Arms
Domain-separated ViDoRe v3 synthetic training arms for finance and industrial adaptation.
The Hub dataset uses finance and industrial as dataset configs/subsets. Within each config, splits separate
vlm_in_batch, vlm_ocr_bm25, banana_fullpipe, and hybrid_vlm_ocr_bm25_banana_fullpipe.
Generated at: 2026-06-29T11:49:45.670912+00:00
Total JSONL rows across configs/splits: 151691.
Images are stored once per subset under… See the full description on the dataset page: https://huggingface.co/datasets/vkehfdl1/banana-vidorev3-synthetic-arms.lllab-vision-banana-datasetpico-banana-smolvlm-format-with-rejected-answer
pico-banana-smolvlm-format-with-rejected-answer
Balanced image-level tampering detection dataset in SmolVLM-style format
with chosen/rejected answer pairs, derived from the pico-banana MCQ
pipeline. Suitable for preference learning (e.g. DPO) and RLHF-style training.
Dataset overview
Same as vanloc1808/pico-banana-smolvlm-format, but each example includes a
rejected_answer field: the answer from the counterpart sample (same
edited/original image pair, opposite… See the full description on the dataset page: https://huggingface.co/datasets/vanloc1808/pico-banana-smolvlm-format-with-rejected-answer.nano-banana
Nano-Banana Generated Images
9,457 high-quality images generated using the Nano-Banana model (Google Gemini 2.5 Flash Image Preview).
Dataset Overview
Total Images: 9,457 images
Generation Method: Nano-Banana (Google Gemini 2.5 Flash Image Preview)
Storage Format: Optimized binary (Hugging Face Image type)
File Organization: Normal large parquet files (not chunked)
License: MIT
Schema
Column
Type
Description
id
int
Unique identifier
image
Image… See the full description on the dataset page: https://huggingface.co/datasets/bitmind/nano-banana.VIBE-Banana-ProBANANAThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "fr3",
"total_episodes": 348,
"total_frames": 152076,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:348"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/yio-ye2004/BANANA.imgbedapple_banana_30hz_cmdThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "fr3",
"total_episodes": 262,
"total_frames": 109516,
"total_tasks": 2,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:262"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/yio-ye2004/apple_banana_30hz_cmd.Nano-banana-150kNano-consistent-150k. — the first dataset constructed using Nano-Banana that exceeds 150k high-quality samples, uniquely designed to preserve consistent human identity across diverse and complex editing scenarios
Banana_reviewer3nano-banana-pro-generated-1k
Nano Banana Pro (1K) Dataset
200 AI-generated images at 1K quality.
License: MIT
bananamark-dataset
🍌 Bananamark - Who has the best Bananas?
Google released a model called Nano Banana. We had to know: is it actually good at generating bananas?
Turns out, not as good as FLUX 2 or Seedream 4!
What we did
We tested 11 image generation models on various banana-themed prompts and collected over 20'000 human preferences using the Rapidata Python API. Annotators were asked a simple question:
Which image has the better bananas?
Want to evaluate your own models? Check out… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/bananamark-dataset.BananaImageBD_variety_classification
BananaImageBD Variety Classification
A dataset for variety classification of bananas. The dataset contains raw and augmented versions.The raw dataset contains 2,471 images.Images per class:
Bangla Kola: 444
Champa Kola: 994
Sabri Kola: 509
Sagor Kola: 524
The augmented dataset contains 7,413 images.Images per class:
Bangla Kola: 1,332
Champa Kola: 2,982
Sabri Kola: 1,527
Sagor Kola: 1,572
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/BananaImageBD_variety_classification.nano-banana-pro-generated-1k-clonename: nano-banana-pro-generated-1k-clone
license: mit
pipeline_tag: text-to-image
tasks:
- text-to-image
- image-generation
tags:
- nano-banana
language: en
size_categories:
- n<1K
[!IMPORTANT]
Original Model Link : https://huggingface.co/datasets/ash12321/nano-banana-pro-generated-1k-clonenano-banana-pro-gennano-banana-pro-gen-zh-enFlameF0X/nano-banana-pro-gen-zh-en is a translation of kaupane/nano-banana-pro-gen from Chinese to English
VIBE-Banana-Flashur3e_banana_to_basketThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "ur3e_dual",
"total_episodes": 100,
"total_frames": 52151,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:100"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/cometkim97/ur3e_banana_to_basket.banana_bunch_detection
Banana Bunch Detection
A dataset for object detection of Banana bunches. The dataset contains 2,179 images with 3,718 bounding box annotations across 1 category.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{baglat2025multi,
title={A multi-stage dataset for banana bunch detection and harvesting decision support},
author={Baglat, Preety and Mendon{\c{c}}a, F{\'a}bio and Mostafa, Shanawaz and… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_bunch_detection.banana_variety_classification
Banana Variety Classification
A dataset for variety classification of bananas. The dataset contains raw and augmented versions.The raw dataset contains 1,166 images.Images per class:
Anaji: 209
Bichi: 182
Champa: 136
Deshi: 237
Shagor: 239
Shobri: 163
The augmented dataset contains 6,000 images.Images per class:
Anaji: 1,000
Bichi: 1,000
Champa: 1,000
Deshi: 1,000
Shagor: 1,000
Shobri: 1,000
This dataset is indexed on https://project-agml.github.io/ as part of the AgML… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_variety_classification.banana_disease_classification_tanzania
Banana Disease Classification Tanzania
A dataset for classification of banana leaf diseases. The dataset contains 16,092 images across 3 classes: black_sigatoka, fusarium_wilt, healthy.Images per class:
black_sigatoka: 5,767
fusarium_wilt: 4,697
healthy: 5,628
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{mduma2023dataset,
title={Dataset of banana leaves and stem images for object detection… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_disease_classification_tanzania.nano-banana-synthetic-images-1500
Overview
This dataset contains 1,500 images generated via Nano Banana. It is designed for Visual Forensics tasks.
Primary Format: JPG
License: CC BY 4.0
SynthID Status: Protected
Dataset Characteristics
Content: This is a highly varied dataset containing a wide mix of subjects, styles, and prompts. It is not limited to a single domain.
Class: 100% AI-Generated (Fake).
Note for Classification: There are NO real images in this dataset. If you are training a binary… See the full description on the dataset page: https://huggingface.co/datasets/SaunakSS/nano-banana-synthetic-images-1500.banana-bunch-yunetbanana_bunch_maturity_classification
Banana Bunch Maturity Classification
A dataset for mautrity classification of banana bunches. The dataset contains 2,685 images across 2 classes: Cut, Keep.
Images per class:
Cut: 1,143
Keep: 1,542
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{baglat2025multi,
title={A multi-stage dataset for banana bunch detection and harvesting decision support},
author={Baglat, Preety and Mendon{\c{c}}a… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_bunch_maturity_classification.Musa_banana_tier_classification
Musa Banana Tier Classification
This dataset contains real RGB images of banana tiers (post-harvest segments of Musa acuminata bunches) captured in a controlled laboratory environment across locations in the Philippines. Images were acquired using a fixed-position A4Tech PK-910H camera, providing standardized visual data for tier classification research in agricultural settings. The dataset contains 1,164 images across 4 classes: 1, 2, 3, 4.Images per class:
1: 390
2: 294
3:… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/Musa_banana_tier_classification.pick-and-place-the-banana-for-franka-research3
Pick and Place the Banana for Franka Research 3
This repository contains Franka Research 3 robot data for the task:
pick up the banana and place it into the plate
The data was converted from local ROS bag recordings into OpenVLA-style
intermediate episodes, no-op-trimmed intermediate episodes, and RLDS / TFDS
training data.
Repository Contents
intermediate/
intermediate_no_noops_hf/
rlds_no_noops/
manifests/
rlds_dataset_builder/
OPENVLA_FRANKA3_DATASET.md… See the full description on the dataset page: https://huggingface.co/datasets/ww-249/pick-and-place-the-banana-for-franka-research3.banana_leaf_disease_classification
Banana Leaf Disease Classification
A dataset for disease classification of Banana Leaves. The dataset contains 1,288 images across 3 classes: healthy, segatoka, xamthomonas.Images per class:
healthy: 154
segatoka: 320
xamthomonas: 814
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{genet2024sigatoka,
title={Sigatoka and xanthomonas banana leaf disease detection via transfer learning}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_leaf_disease_classification.