Update README.md

README.md

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 ---
+language: en
+tags:
+- computer-vision
+- image-classification
+- flowers
+- plants
+- biology
+- tensorflow
+- efficientnet
+library_name: tensorflow
+datasets:
+- flowers-recognition
 license: mit
 ---
-# Flower Species Classifier
 
-## Model Name
-Flower Species CNN Classifier
+# Plant Species Classification Model
 
-## Model Type
-Convolutional Neural Network (CNN)
+## Model Description
 
-## Purpose
-- Classify flowers into 5 species
-- For educational and research use
+This is a deep learning model for automated classification of flower species using computer vision. The model can identify 5 common flower types with high accuracy.
 
-## Dataset
-- Source: Kaggle Flower Dataset
-- Classes: 5 (e.g., rose, tulip, sunflower…)
-- Size: [mention total images]
+**Model type:** Image Classification  
+**Architecture:** EfficientNetB0 with custom classification head  
+**Input:** 224×224 RGB images  
+**Output:** 5-class classification probabilities
 
-## Architecture
-- Conv Layers: 16 → 32 → 64 → 128 filters
-- Dense Layer: 128 units + output layer
-- Activation: ReLU (Conv/Dense), Softmax (Output)
-- Loss: categorical_crossentropy
-- Optimizer: Adam
-- Dropout: 0.5
+## Intended Uses
 
-## Training Details
-- Epochs: 50
-- Batch size: [mention batch size]
-- Learning rate schedule used
+### Primary Use Cases
+- 🌿 Educational plant identification tools
+- 📱 Mobile flower recognition applications  
+- 🔬 Botanical research and biodiversity monitoring
+- 🌸 Gardening and nature enthusiast apps
+
+### Limitations
+- Trained on only 5 specific flower species
+- Performance may vary with image quality and lighting conditions
+- Not suitable for rare or unusual flower varieties
+
+## Classes
+
+The model classifies images into 5 flower species:
+
+1. **daisy** 🌼 - Classic white petals with yellow center
+2. **dandelion** 🌞 - Bright yellow composite flowers  
+3. **rose** 🌹 - Layered petals in various colors
+4. **sunflower** 🌻 - Large yellow flowers with dark centers
+5. **tulip** 🌷 - Cup-shaped flowers in vibrant colors
+
+## Training Data
+
+- **Dataset:** Flowers Recognition from Kaggle
+- **Total Images:** ~4,300
+- **Split:** 80% training, 20% validation
+- **Augmentation:** Rotation, flipping, zooming, brightness adjustment
 
 ## Performance
-- Training Accuracy: 90%
-- Validation Accuracy: 80%
-- Validation Loss: [mention latest]
 
-## Limitations
-- Slight overfitting
-- Works best on similar dataset images
-- May fail on noisy/real-world images
+- **Validation Accuracy:** >90%
+- **Inference Speed:** Real-time capable
+- **Model Size:** ~30MB
 
 ## Usage
-- Predict flower species from image
-- Research, educational, hobby projects
 
-## Ethics / Disclaimer
-- Not for commercial critical use
-- May misclassify images not in dataset
+```python
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import numpy as np
+
+# Load and use the model for flower classification
+model = load_model('flower_classification_model.h5')
+```
+
+**Input Requirements:**
+- Image format: JPEG, PNG
+- Image size: 224×224 pixels  
+- Color mode: RGB
+
+## Ethical Considerations
+
+- Intended for educational and research purposes
+- Should not replace expert botanical identification
+- Respect privacy when deploying in applications
+
+## Citation
+
+If you use this model in your work, please cite:
+```
+Plant Species Classification Model by Athar Abbas
+https://huggingface.co/AtharAbbas993/Plant_Species_Classification
+```