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Running
on
CPU Upgrade
| import gradio as gr | |
| import kornia as K | |
| from skimage import io | |
| from kornia.contrib import ImageStitcher | |
| import kornia.feature as KF | |
| def enhance(file_1, file_2): | |
| img_1 = K.image_to_tensor(io.imread(file_1), False).float() / 255. | |
| img_2 = K.image_to_tensor(io.imread(file_2), False).float() / 255. | |
| IS = ImageStitcher(KF.LoFTR(pretrained='outdoor'), estimator='ransac') | |
| result = IS(img_1, img_2) | |
| return K.tensor_to_image(result[0]) | |
| examples = [ | |
| ['examples/foto1B.jpg'], | |
| ['examples/foto1A.jpg'], | |
| ] | |
| inputs = [ | |
| gr.inputs.Image(type='filepath', label='Input Image'), | |
| gr.inputs.Image(type='filepath', label='Input Image'), | |
| ] | |
| outputs = [ | |
| gr.outputs.Image(type='filepath', label='Output Image'), | |
| ] | |
| title = "Image Stitching using Kornia and LoFTR" | |
| demo_app = gr.Interface( | |
| fn=enhance, | |
| inputs=inputs, | |
| outputs=outputs, | |
| title=title, | |
| examples=examples, | |
| live=True, | |
| ) | |
| demo_app.launch() | |