Vineyard Scene Recognition Data
#Object Detection #Image Classification #Agricultural Monitoring #Environmental Protection #Precision Planting
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-14
AI Analysis & Value Prop
The current agricultural industry faces multifaceted challenges such as climate change, pests, and diseases. Farmers need efficient information to make planting decisions. Existing solutions often rely on manual experience and lack systematic data support, leading to insufficient decision accuracy. This dataset aims to assist AI models in better recognizing orchard planting patterns and environmental features by providing images of vineyard scenes under different seasons and lighting conditions, thus enhancing the intelligence level of agricultural production. Data collection is mainly accomplished using high-resolution cameras to capture diverse environmental variables across various seasons and lighting conditions. To ensure data quality, multiple rounds of annotation, consistency checks, and expert reviews were conducted to ensure the accuracy of the labeling information for each image. The data is stored in JPG format and is organized by season and lighting conditions.
Dataset Insights
Sample Examples
7bd3336d**.jpg|5616*3744|4.08 MB
74dd2d51**.jpg|4000*6000|2.99 MB
02e74897**.jpg|5616*3744|3.77 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| season | string | The season during which the image was captured, such as spring, summer, autumn, or winter. |
| illumination_condition | string | The lighting condition during image capture, such as sunny, cloudy, or sunset. |
| weather_condition | string | The weather condition at the time of image capture, such as clear, cloudy, or rainy. |
| grape_variety | string | The variety of grapes appearing in the image, if applicable, such as Cabernet Sauvignon or Chardonnay. |
| vineyard_location | string | The specific location or region of the vineyard where the image was captured. |
| growth_stage | string | The growth stage of the grapevines when the image was taken, such as budburst, flowering, or fruiting. |
| image_quality | string | The quality evaluation of the image, such as clear, blurry, or overexposed. |
| feature_description | text | A description of key features visible in the image, such as the density of grape clusters. |
| fruit_color | string | The color of the grape fruits visible in the image, such as green or purple. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What agricultural applications is the vineyard scene recognition dataset suitable for?
- This dataset is suitable for applications such as orchard management, crop health monitoring, and yield prediction.
- What are the features of the vineyard scene recognition dataset?
- The dataset contains high-quality images of vineyards captured under different seasonal and lighting conditions, facilitating precise scene recognition by AI models.
- How can the vineyard scene recognition dataset be used for orchard analysis?
- The dataset can be used to train AI models for tree recognition, disease detection, and growth stage analysis, thereby enhancing orchard management efficiency.
- How does the vineyard scene recognition dataset support AI orchard analysis?
- By providing a diverse range of image data, AI can learn to recognize different objects and scenes in vineyards, enhancing the accuracy of model analysis.
- Why choose the vineyard scene recognition dataset to train AI models?
- Because this dataset covers vineyard images under various environmental conditions, enabling AI models to be robust and accurate in diverse real-world scenarios.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Vineyard Scene Recognition Data},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/f8e43b98bbe3f2fda4704c40c0fa2dc0},
urldate={2025-09-15},
keywords={vineyard dataset, agricultural object detection, scene recognition, AI agriculture},
version={1.0}
}Using this in research? Please cite us.
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