Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+---
+# 🐔 EfficientNetV2S Poultry Feces Classifier
+
+A convolutional neural network model based on **EfficientNetV2S** for classifying chicken fecal images into 4 common conditions:
+
+* **Coccidiosis**
+* **Healthy**
+* **Newcastle Disease**
+* **Salmonella**
+
+This model is designed to support smart poultry farming by enabling early detection of diseases through image-based feces analysis.
+
+## 🧬 Model Architecture
+
+* Base: `EfficientNetV2S` (pretrained on ImageNet, frozen then fine-tuned)
+* Head:
+
+  * `GlobalAveragePooling2D`
+  * `Dense(128) + BatchNorm + ReLU + Dropout(0.3)`
+  * `Dense(4, activation='softmax')`
+
+## 🧪 Training & Evaluation
+
+* Optimizer: Adam
+* Loss: Categorical Crossentropy
+* Metric: Accuracy
+* Dataset:
+
+  * Source: [Jayavrinda et al., 2023](https://doi.org/10.34740/KAGGLE/DS/3951043)
+  * 4 classes, resized to 224x224 pixels
+  * Train/Val/Test sampling (3k/400/400 per class)
+* EarlyStopping was used to monitor validation accuracy
+* Accuracy on validation set: **\~90%+** (see notebook for full results)
+
+## 🗄️ Example Usage
+
+```python
+from tensorflow.keras.models import load_model
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+model = load_model("path/to/your_model.h5")
+
+def preprocess(image_path):
+    img = Image.open(image_path).resize((224, 224))
+    img_array = np.array(img) / 255.0
+    return np.expand_dims(img_array, axis=0)
+
+pred = model.predict(preprocess("feces.jpg"))
+class_names = ["Coccidiosis", "Healthy", "Newcastle", "Salmonella"]
+print("Prediction:", class_names[np.argmax(pred)])
+```
+
+## 📜 Citation
+
+If you use this model or dataset, please cite:
+
+> Jayavrinda Vrindavanam, Pradeep Kumar, Gaurav Kamath, Chandrashekar N, and Govind Patil. (2023). *Poultry Pathology Visual Dataset* \[Data set]. Kaggle. [https://doi.org/10.34740/KAGGLE/DS/3951043](https://doi.org/10.34740/KAGGLE/DS/3951043)
+
+---
+
+Beyond the Outliers
+
+Datathon 2025