---
license: mit
task_categories:
- object-detection
language:
- en
tags:
- yolov5
- object_detection
- crops/plant_25k_images
- computer_vision
pretty_name: leaflogic_dataset
size_categories:
- 10K<n<100K
---
# Open-Source Crop/Plant Object Detection Dataset

*Note: If you need this dataset in any other format, DM me on LinkedIn or ask in the discussions box. I will provide it ASAP.*

## Introduction
I am excited to open-source this dataset to help developers, researchers, and machine learning enthusiasts build object detection models for agricultural applications. This dataset consists of annotated images of **100 different crops/plants**, providing a valuable resource for training and evaluating object detection models.

*Remember: This dataset is in .zip format, extract the .zip file and dataset is yours*

## Dataset Details
The dataset is available on **[Hugging Face](https://huggingface.co/datasets/devshaheen/100_crops_plants_object_detection_25k_image_dataset)** and contains three splits:
- **Train:** 17,553 images with corresponding labels
- **Validation:** 4,990 images with corresponding labels
- **Test:** 2,458 images with corresponding labels

Each split contains:
- Images
- Labels (in YOLOv5 format)
- A `data.yaml` file for configuration

## Annotation
The dataset has been annotated using **Roboflow**, ensuring high-quality bounding box annotations for each crop/plant category.  
All annotations follow the **YOLOv5 format**, making it easy to train models with YOLO-based architectures.  

## Plant/Crop Categories
This dataset includes **100 different crops/plants**, covering a wide range of agricultural produce:
*Note: Each category has atleast 250 images and 328 bounding box annotations respectively*

1. Zingiber officinale (Ginger)  
2. Almonds  
3. Aloe Vera  
4. Apple  
5. Apricot  
6. Areca Nut  
7. Ashwagandha  
8. Avocado  
9. Bamboo  
10. Banana  
11. Beetroot  
12. Bell Pepper (Capsicum)  
13. Bitter Gourd  
14. Black Pepper  
15. Blackberry  
16. Blackgram  
17. Blueberry  
18. Bottle Gourd  
19. Brinjal (Eggplant)  
20. Broccoli  
21. Cabbage  
22. Cactus  
23. Cardamom  
24. Carrot  
25. Cashew  
26. Cassava  
27. Cauliflower  
28. Chamomile  
29. Cherry  
30. Chili Pepper  
31. Cinnamon  
32. Coconut  
33. Coffee Beans  
34. Coriander  
35. Cotton  
36. Cucumber  
37. Date Palm  
38. Dates  
39. Dragon Fruit  
40. Figs (Anjeer)  
41. Garlic  
42. Grapes  
43. Green Gram (Mung Bean)  
44. Groundnut (Peanut)  
45. Guava  
46. Jaggery  
47. Jute  
48. Kidney Bean  
49. Kiwi  
50. Lavender  
51. Lemon  
52. Lychee  
53. Maize  
54. Mango  
55. Mint Herb  
56. Mushroom  
57. Muskmelon  
58. Mustard Crop  
59. Oats  
60. Okra (Ladyfinger)  
61. Onion  
62. Orange  
63. Orchid (Orchidaceae)  
64. Papaya  
65. Pea  
66. Peach  
67. Pear  
68. Pineapple  
69. Pista (Pistachio)  
70. Plum  
71. Pomegranate  
72. Pomelo  
73. Potato  
74. Pumpkin  
75. Radish  
76. Raspberry  
77. Rice  
78. Rose  
79. Rosemary  
80. Rubber Plant  
81. Safflower  
82. Saffron  
83. Sesame  
84. Sorghum  
85. Soursop  
86. Soybean  
87. Spinach  
88. Starfruit (Carambola)  
89. Strawberry  
90. Sugar Apple  
91. Sugarcane  
92. Sunflower  
93. Sweet Potato  
94. Tea  
95. Tomato  
96. Tulip  
97. Turmeric  
98. Walnut  
99. Watermelon  
100. Wheat  

## Use the dataset
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("devshaheen/100_crops_plants_object_detection_25k_image_dataset")

# Check the dataset structure
print(dataset)
```


## License
This dataset is released under the **MIT License**, allowing free use for both research and commercial projects. Please credit this repository if you use it in your work.

## Credits
Wherever this dataset is used, credits should be given to:
- **Shaheen Nabi**: [LinkedIn](https://www.linkedin.com/in/shaheennabi/)
- **Izhar Ashiq**: [LinkedIn](https://in.linkedin.com/in/izharashiq)

## Contact
For any inquiries, you can DM on LinkedIn or use the discussion box on GitHub.

Let's build the future of AI-powered agriculture together! 🚀🌱
---