| import gradio as gr | |
| import tensorflow as tf | |
| model = tf.keras.models.load_model('best_model.h5') | |
| categories = ["Normal","Pneumonia", "Tubercolosis"] | |
| def classify(img): | |
| img = img.reshape((-1, 224, 224, 3)) | |
| pred = model.predict(img)[0] | |
| return {categories[i]: float(pred[i]) for i in range(3)} | |
| image = gr.inputs.Image(shape=(224, 224)) | |
| label = gr.outputs.Label(num_top_classes=3) | |
| examples = ["Normal.png", "Tuberculosis.png", "Pneumonia.jpeg"] | |
| intf = gr.Interface(classify,inputs=image, outputs=label, examples=examples, capture_session=True) | |
| intf.launch(inline=False) | |