🩻 X-ray Pneumonia Classifier

This is a binary image classification model trained to detect Pneumonia from chest X-ray images using EfficientNetB3 as the backbone.

📊 Model Details

Architecture: EfficientNetB3 (Keras Applications)
Input: 300x300 RGB chest X-ray images
Output: Binary classification (Pneumonia vs Normal)
Framework: TensorFlow / Keras
Test Accuracy: 80.95%
License: MIT

🧠 Dataset

The model was trained on a filtered subset of the COVID-19 Chest X-ray Dataset, which contains labeled chest X-ray images for Pneumonia and Normal classes.

⚙️ Usage

You can load and use the model with TensorFlow/Keras for inference:

from tensorflow.keras.models import load_model
model = load_model("xray_classifier_model.keras")

# preprocess your image to 300x300 RGB and normalize to [0,1]
# then run
pred = model.predict(preprocessed_image)