| 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) |
|
|
