Create app.py

app.py

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+import matplotlib.pyplot as plt
+import cv2
+import kornia as K
+import kornia.feature as KF
+import numpy as np
+import torch
+from kornia_moons.feature import *
+import gradio as gr
+
+def load_torch_image(fname):
+    img = K.image_to_tensor(cv2.imread(fname), False).float() /255.
+    img = K.color.bgr_to_rgb(img)
+    return img
+def inference(file1,file2):
+    fname1 = file1.name
+    fname2 = file2.name
+
+    img1 = load_torch_image(fname1)
+    img2 = load_torch_image(fname2)
+
+
+    matcher = KF.LoFTR(pretrained='outdoor')
+
+    input_dict = {"image0": K.color.rgb_to_grayscale(img1), # LofTR works on grayscale images only 
+                "image1": K.color.rgb_to_grayscale(img2)}
+
+    with torch.no_grad():
+        correspondences = matcher(input_dict)
+    mkpts0 = correspondences['keypoints0'].cpu().numpy()
+    mkpts1 = correspondences['keypoints1'].cpu().numpy()
+    H, inliers = cv2.findFundamentalMat(mkpts0, mkpts1, cv2.USAC_MAGSAC, 0.5, 0.999, 100000)
+    inliers = inliers > 0
+    fig, ax = plt.subplots()
+
+    draw_LAF_matches(
+        KF.laf_from_center_scale_ori(torch.from_numpy(mkpts0).view(1,-1, 2),
+                                    torch.ones(mkpts0.shape[0]).view(1,-1, 1, 1),
+                                    torch.ones(mkpts0.shape[0]).view(1,-1, 1)),
+
+        KF.laf_from_center_scale_ori(torch.from_numpy(mkpts1).view(1,-1, 2),
+                                    torch.ones(mkpts1.shape[0]).view(1,-1, 1, 1),
+                                    torch.ones(mkpts1.shape[0]).view(1,-1, 1)),
+        torch.arange(mkpts0.shape[0]).view(-1,1).repeat(1,2),
+        K.tensor_to_image(img1),
+        K.tensor_to_image(img2),
+        inliers,
+        draw_dict={'inlier_color': (0.2, 1, 0.2),
+                'tentative_color': None, 
+                'feature_color': (0.2, 0.5, 1), 'vertical': False}, ax=ax)
+
+    fig.savefig('example.jpg',dpi=199)
+    return 'example.jpg'
+
+
+title = "Kornia-Loftr"
+description = "demo for Anime2Sketch. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.05703'>Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis</a> | <a href='https://github.com/Mukosame/Anime2Sketch'>Github Repo</a></p>"
+
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="file", label="Input1"),gr.inputs.Image(type="file", label="Input2")], 
+    gr.outputs.Image(type="file", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    enable_queue=True
+    ).launch(debug=True)