Duplicate from jameelkhalidawan/Plant_Detection_Classification

Co-authored-by: jameelkhalid <jameelkhalidawan@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,61 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+train_split/val.cache filter=lfs diff=lfs merge=lfs -text
+train_split/train.cache filter=lfs diff=lfs merge=lfs -text

Plants_Dataset.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c6a3e221223c9036aabdc5a3a35a96f578331426478980c7228a270307665b3
+size 30315889892

README.md

@@ -0,0 +1,166 @@
+# Plant Species Classification Dataset
+
+A comprehensive dataset containing 64 different plant species with high-quality images for machine learning and computer vision applications.
+Model Trainig code and trainned model with detailed performance analysis is present on the Github
+https://github.com/jameelkhalidawan/Plant-Detection-Model-using-Yolo
+
+## Dataset Overview
+
+This dataset is designed for plant species classification tasks and contains images of various plant species organized in a structured format suitable for training deep learning models.
+
+### Key Statistics
+
+- **Total Classes**: 64 plant species
+- **Total Images**: 152,042 images
+- **Image Format**: JPG
+- **Dataset Split**:
+  - Training: 106,395 images
+  - Validation: 22,779 images  
+  - Test: 22,868 images
+
+## Dataset Structure
+
+```
+Plants_Datadet/
+├── train/                    # Training data (106,395 images)
+│   ├── [Plant Species 1]/    # Each folder contains images of one species
+│   ├── [Plant Species 2]/
+│   └── ...
+├── val/                      # Validation data (22,779 images)
+│   ├── [Plant Species 1]/
+│   ├── [Plant Species 2]/
+│   └── ...
+├── test/                     # Test data (22,868 images)
+│   ├── [Plant Species 1]/
+│   ├── [Plant Species 2]/
+│   └── ...
+├── train_split/              # Additional split for training (generated by training code)
+│   ├── train/
+│   ├── val/
+│   ├── train.cache
+│   └── val.cache
+└── image_counts.xlsx         # Detailed image count statistics
+```
+
+## Plant Species Included
+
+The dataset contains 64 diverse plant species including:
+
+### Trees and Shrubs
+- Acacia dealbata Link
+- Liriodendron tulipifera L
+- Nandina domestica Thunb
+- Pyracantha coccinea M.Roem
+- Schefflera arboricola (Hayata) Merr
+- Smilax aspera L
+- Trachelospermum jasminoides (Lindl.) Lem
+- Zamioculcas zamiifolia (Lodd.) Engl
+
+### Herbs and Wildflowers
+- Aegopodium podagraria L
+- Anemone alpina L
+- Anemone hepatica L
+- Anemone hupehensis (Lemoine) Lemoine
+- Anemone nemorosa L
+- Angelica sylvestris L
+- Barbarea vulgaris R.Br
+- Cirsium arvense (L.) Scop
+- Cirsium vulgare (Savi) Ten
+- Cymbalaria muralis P.Gaertn., B.Mey. & Scherb
+- Dryopteris filix-mas (L.) Schott
+- Epipactis helleborine (L.) Crantz
+- Fragaria vesca L
+- Helminthotheca echioides (L.) Holub
+- Humulus lupulus L
+- Hypericum androsaemum L
+- Hypericum calycinum L
+- Kniphofia uvaria (L.) Hook
+- Lactuca serriola L
+- Lamium album L
+- Lamium galeobdolon (L.) L
+- Lamium maculatum (L.) L
+- Lamium purpureum L
+- Lapsana communis L
+- Lupinus polyphyllus Lindl
+- Melilotus albus Medik
+- Mercurialis annua L
+- Nymphaea alba L
+- Ophrys apifera Huds
+- Pancratium maritimum L
+- Papaver rhoeas L
+- Papaver somniferum L
+- Perovskia atriplicifolia Benth
+- Trifolium incarnatum L
+
+### Succulents and Sedums
+- Sedum acre L
+- Sedum album L
+- Sedum rupestre L
+- Sedum sediforme (Jacq.) Pau
+
+### Ornamental Plants
+- Anthurium andraeanum Linden ex André
+- Fittonia albivenis (Lindl. ex Veitch) Brummitt
+- Lavandula angustifolia Mill
+- Lavandula stoechas L
+- Pelargonium graveolens L'Hér
+- Pelargonium inquinans (L.) Aiton
+- Pelargonium zonale (L.) L'Hér
+- Pelargonium zonale (L.) L'Hér. ex Aiton
+- Punica granatum L
+- Tagetes erecta L
+- Tagetes patula L
+
+### Vegetables and Fruits
+- Cucurbita maxima Duchesne
+- Cucurbita pepo L
+
+### Tradescantia Varieties
+- Tradescantia fluminensis Vell
+- Tradescantia pallida (Rose) D.R.Hunt
+- Tradescantia spathacea Sw
+- Tradescantia virginiana L
+- Tradescantia zebrina Bosse
+
+## Image Characteristics
+
+- **Format**: JPG
+- **Naming Convention**: Images use hash-based filenames (e.g., `0038b49e0352646885a8899be350813d927f34a5.jpg`)
+- **Quality**: High-quality images suitable for detailed plant identification
+- **Content**: Various parts of plants including flowers, leaves, stems, and full plant views
+
+## Usage
+
+This dataset is suitable for:
+
+1. **Plant Species Classification**: Train models to identify and classify different plant species
+2. **Computer Vision Research**: Develop and test image classification algorithms
+3. **Botanical Studies**: Analyze plant characteristics and features
+4. **Educational Applications**: Create learning tools for plant identification
+5. **Agricultural Applications**: Assist in crop and weed identification
+
+
+## Dataset Splits
+
+The dataset is pre-split into training, validation, and test sets to ensure proper model evaluation:
+
+- **Training Set**: Used for model training and parameter optimization
+- **Validation Set**: Used for hyperparameter tuning and model selection
+- **Test Set**: Used for final model evaluation and performance assessment
+
+## Additional Files
+
+- `image_counts.xlsx`: Contains detailed statistics about the number of images per class
+- `train_split/`: Contains additional splits generated during the training process with cache files for faster data loading
+
+## Citation
+
+If you use this dataset in your research or projects, please cite it appropriately and acknowledge the contributors.
+
+## License
+
+Please check the license terms before using this dataset for commercial purposes.
+
+---
+
+*This dataset provides a comprehensive collection of plant species images suitable for various machine learning and computer vision applications in botany, agriculture, and environmental studies.*