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---
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! 🚀🌱
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