Datasets:
Tasks:
Image Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
Target detection
image classification
Agricultural monitoring
crop identification
smart agriculture
License:
Commit ·
d17b24c
verified ·
0
Parent(s):
initial commit
Browse files- .gitattributes +60 -0
- README.md +56 -0
.gitattributes
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
*.7z filter=lfs diff=lfs merge=lfs -text
|
| 2 |
+
*.arrow filter=lfs diff=lfs merge=lfs -text
|
| 3 |
+
*.avro filter=lfs diff=lfs merge=lfs -text
|
| 4 |
+
*.bin filter=lfs diff=lfs merge=lfs -text
|
| 5 |
+
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
| 6 |
+
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
| 7 |
+
*.ftz filter=lfs diff=lfs merge=lfs -text
|
| 8 |
+
*.gz filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
| 10 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 11 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
| 12 |
+
*.lz4 filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.mds filter=lfs diff=lfs merge=lfs -text
|
| 14 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 15 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.npz filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 22 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
# Audio files - uncompressed
|
| 40 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 42 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
# Audio files - compressed
|
| 44 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
|
| 48 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 49 |
+
# Image files - uncompressed
|
| 50 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 53 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 54 |
+
# Image files - compressed
|
| 55 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 56 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 57 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
| 58 |
+
# Video files - compressed
|
| 59 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
| 60 |
+
*.webm filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
|
@@ -0,0 +1,56 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- Target detection
|
| 4 |
+
- image classification
|
| 5 |
+
- Agricultural monitoring
|
| 6 |
+
- crop identification
|
| 7 |
+
- smart agriculture
|
| 8 |
+
license: cc-by-nc-sa-4.0
|
| 9 |
+
task_categories:
|
| 10 |
+
- image-classification
|
| 11 |
+
language:
|
| 12 |
+
- en
|
| 13 |
+
pretty_name: Asparagus Identification Dataset
|
| 14 |
+
size_categories:
|
| 15 |
+
- 1B<n<10B
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
# Asparagus Identification Dataset
|
| 19 |
+
|
| 20 |
+
The current agricultural industry faces challenges in efficient crop monitoring and recognition. Traditional manual detection methods are inefficient and prone to errors. Existing solutions often rely on empirical judgment without scientific model support. This dataset aims to provide diverse asparagus images to help train automatic recognition models, improving the accuracy and efficiency of crop monitoring. The dataset includes images of asparagus from different varieties, angles, and lighting conditions. High-resolution cameras were used during the data collection process under natural light conditions and in various environments to ensure diversity. For quality control, all annotations were reviewed in multiple rounds and consistency checks were conducted to ensure the accuracy and reliability of the annotations. The data is stored in JPEG format with a clear organizational structure for ease of use in subsequent model training and testing. The core advantage of this dataset is its high annotation accuracy and consistency, with annotation accuracy exceeding 95%, and by introducing new data augmentation techniques, it effectively enhances the model's generalization ability. Using this dataset, the model's accuracy in asparagus recognition tasks improved by about 15%, significantly optimizing the efficiency and reliability of agricultural monitoring.
|
| 21 |
+
|
| 22 |
+
## Technical Specifications
|
| 23 |
+
|
| 24 |
+
| Field | Type | Description |
|
| 25 |
+
| :--- | :--- | :--- |
|
| 26 |
+
| file_name | string | File name |
|
| 27 |
+
| quality | string | Resolution |
|
| 28 |
+
| asparagus_species | string | The species of asparagus in the image. |
|
| 29 |
+
| light_condition | string | The lighting condition during which the image was captured, such as natural light, cloudy, or nighttime. |
|
| 30 |
+
| asparagus_count | int | The number of asparagus visible in the image. |
|
| 31 |
+
| growth_stage | string | The growth stage of the asparagus in the image, such as sprouting or mature. |
|
| 32 |
+
|
| 33 |
+
## Compliance Statement
|
| 34 |
+
|
| 35 |
+
<table>
|
| 36 |
+
<tr>
|
| 37 |
+
<td>Authorization Type</td>
|
| 38 |
+
<td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
|
| 39 |
+
</tr>
|
| 40 |
+
<tr>
|
| 41 |
+
<td>Commercial Use</td>
|
| 42 |
+
<td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
|
| 43 |
+
</tr>
|
| 44 |
+
<tr>
|
| 45 |
+
<td>Privacy and Anonymization</td>
|
| 46 |
+
<td>No PII, no real company names, simulated scenarios follow industry standards</td>
|
| 47 |
+
</tr>
|
| 48 |
+
<tr>
|
| 49 |
+
<td>Compliance System</td>
|
| 50 |
+
<td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
|
| 51 |
+
</tr>
|
| 52 |
+
</table>
|
| 53 |
+
|
| 54 |
+
## Source & Contact
|
| 55 |
+
|
| 56 |
+
If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/d301dd7988a381a8dbd9fffb680ea7c9?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com
|