| from skimage.util import montage as montage2d | |
| from utils import load_model, preprocess_image, attempt_download_from_hub | |
| import matplotlib.pyplot as plt | |
| import gradio as gr | |
| model_path = 'deprem-ml/deprem-keras-satellite-semantic-mapping' | |
| def keras_inference(img_data, model_path): | |
| model_path = attempt_download_from_hub(model_path) | |
| seg_model = load_model(model_path) | |
| out_img = preprocess_image(img_data) | |
| pred_y = seg_model.predict(out_img) | |
| plt.imshow(montage2d(pred_y[:, :, :, 0]), cmap = 'bone_r') | |
| plt.savefig('output.png') | |
| return 'output.png' | |
| inputs = [ | |
| gr.Image(type='filepath', label='Image'), | |
| gr.Dropdown([model_path], value=model_path, label='Model Path') | |
| ] | |
| outputs = gr.Image(label='Segmentation') | |
| examples = [ | |
| ['data/testv1.jpg', model_path], | |
| ['data/testv2.jpg', model_path], | |
| ['data/testv3.jpg', model_path], | |
| ] | |
| title = 'Segmenting Buildings in Satellite Images with Keras' | |
| demo_app = gr.Interface( | |
| keras_inference, | |
| inputs, | |
| outputs, | |
| title=title, | |
| examples=examples, | |
| cache_examples=True, | |
| ) | |
| demo_app.launch(debug=True, enable_queue=True) | |