Datasets:

devshaheen
/

100_crops_plants_object_detection_25k_image_dataset

@@ -1,178 +1,147 @@
----
-dataset_name: "100 Crops/Plants Object Detection 25K Image Dataset"
-tags:
-  - object-detection
-  - agriculture
-  - crops
-  - plants
-  - open-source
-  - YOLOv5
-language: "en"
-license: "MIT"
-size_categories:
-  - "25K+ images"
-task_categories:
-  - "object-detection"
-dataset_summary: |
-  This dataset consists of **25,000+ high-quality annotated images** of **100 different crops/plants**, designed to train object detection models for agricultural applications. The annotations follow the **YOLOv5 format**, making it easy to use for training deep learning models.
-dataset_structure: |
-  The dataset is provided in a **zip file**, which must be extracted before use. It is split into three subsets:
-  - **Train:** 17,553 images with labels
-  - **Validation:** 4,990 images with labels
-  - **Test:** 2,458 images with labels
-  Each split contains:
-  - **Images** (JPG/PNG format)
-  - **Labels** (YOLOv5 `.txt` format)
-  - **`data.yaml`** configuration file for YOLO training
-annotation_details: |
-  - **Annotated using Roboflow**
-  - **Bounding boxes for each crop/plant category**
-  - **Preprocessed for YOLOv5-based models**
-  - Each image has a corresponding `.txt` annotation file with bounding boxes in the following format:
-    ```
-    <class_id> <x_center> <y_center> <width> <height>
-    ```
-  - All values are **normalized between 0 and 1**.
-plant_categories: |
-  This dataset includes **100 crop/plant categories**, providing labeled images for agricultural AI applications:
-  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
-usage: |
-  You can load this dataset using the Hugging Face `datasets` library:
-  ```python
-  from datasets import load_dataset
-  dataset = load_dataset("devshaheen/100_crops_plants_object_detection_25k_image_dataset")
-## Clone Dataset
-Or, clone the dataset manually:
-```bash
-git clone https://huggingface.co/datasets/devshaheen/100_crops_plants_object_detection_25k_image_dataset
-## License Details
-This dataset is released under the **MIT License**, allowing free use for both research and commercial projects. Please credit the authors when using it.
-## Citation
-If you use this dataset, please credit:
-- **Shaheen Nabi** ([LinkedIn](https://www.linkedin.com/in/shaheennabi/))
-- **Izhar Ashiq** ([LinkedIn](https://in.linkedin.com/in/izharashiq))
 ## Contact
-For any inquiries, feel free to reach out via LinkedIn or start a discussion on Hugging Face.
-🔗 **Hugging Face Profile**: [https://huggingface.co/devshaheen](https://huggingface.co/devshaheen)
-## Note
-💡 **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. 🚀🌱

+# 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:
+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
+## Download Dataset
+Clone this repository to access the dataset:
+   ```bash
+   git clone https://github.com/shaheennabi/My_Datasets/tree/main/25k_Crops_Plants_object_detection_dataset_open-source
+   ```
+## 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! 🚀🌱