| import gradio as gr | |
| from tensorflow.keras.models import load_model | |
| from PIL import Image | |
| import numpy as np | |
| model = load_model('xray_image_classifier_model.keras') | |
| def predict_image(img): | |
| img = img.resize((150, 150)) | |
| img = np.array(img) / 255.0 | |
| img = np.expand_dims(img, axis=0) | |
| prediction = model.predict(img) | |
| label = 'Pneumonia' if prediction > 0.5 else 'Normal' | |
| return label | |
| iface = gr.Interface( | |
| fn=predict_image, | |
| inputs=gr.inputs.Image(type="pil"), | |
| outputs="text", | |
| title="X-ray Image Classifier", | |
| description="Upload an X-ray image to classify it as 'Pneumonia' or 'Normal'." | |
| ) | |
| iface.launch() | |