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Datasets:
devshaheen
/
100_crops_plants_object_detection_25k_image_dataset

Tasks:
Object Detection
Languages:
English
Size:
10K<n<100K
Tags:
yolov5
object_detection
crops/plant_25k_images
computer_vision
License:
Dataset card Files Community
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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 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 

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:

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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