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README.md

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-In recent times, the field of agriculture has been in urgent need of modernizing, since the amount of manual work people need to put in to check if plants are growing correctly is still highly extensive. Despite several advances in agricultural technology, people working in the agricultural industry still need to have the ability to sort and recognize different plants and weeds, which takes a lot of time and effort in the long term. The potential is ripe for this trillion-dollar industry to be greatly impacted by technological innovations that cut down on the requirement for manual labor, and this is where Artificial Intelligence can actually benefit the workers in this field, as the time and energy required to identify plant seedlings will be greatly shortened by the use of AI and Deep Learning. The ability to do so far more efficiently and even more effectively than experienced manual labor, could lead to better crop yields, the freeing up of human inolvement for higher-order agricultural decision making, and in the long term will result in more sustainable environmental practices in agriculture as well.
+# 🌱 Plant Seedlings Classification — AI for Smarter Agriculture  
+
+## 🧩 Overview  
+Agriculture remains one of the most vital yet labor-intensive industries.  
+Farmers and agronomists often spend countless hours identifying seedlings, weeds, and crop health manually.  
+This model leverages **Deep Learning and Computer Vision** to automatically recognize plant species from seedling images —  
+helping accelerate early-stage crop monitoring and enabling precision agriculture.  
+
+---
+
+## 🤖 Model Details  
+- **Model Type:** CNN-based Image Classifier  
+- **Framework:** TensorFlow / Keras  
+- **Dataset:** Plant Seedlings Dataset (12 plant categories)  
+- **Input:** RGB image of a seedling  
+- **Output:** Predicted plant species label  
+
+---
+
+## 🌾 Why It Matters  
+✅ Reduces manual effort in plant identification  
+✅ Boosts accuracy and consistency in seedling detection  
+✅ Supports sustainable, data-driven agriculture  
+✅ Enables automation in large-scale farming and greenhouse monitoring  
+
+---
+
+## 🚀 Example Usage  
+```python
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import numpy as np
+
+model = load_model("plant_seedlings_model.h5")
+
+img = image.load_img("seedling.jpg", target_size=(128, 128))
+x = image.img_to_array(img)
+x = np.expand_dims(x, axis=0) / 255.0
+
+pred = np.argmax(model.predict(x), axis=1)
+print("Predicted plant category:", pred)