Update README.md

README.md

@@ -81,7 +81,7 @@ import torch
 from PIL import Image
 import requests
 
-url = "https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/assets/phototourism_sample_images/london_bridge_78916675_4568141288.jpg?raw=true"
+url = "https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/assets/phototourism_sample_images/london_bridge_19481797_2295892421.jpg?raw=true"
 im1 = Image.open(requests.get(url, stream=True).raw)
 url = "https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/assets/phototourism_sample_images/london_bridge_19481797_2295892421.jpg?raw=true"
 im2 = Image.open(requests.get(url, stream=True).raw)
@@ -103,9 +103,9 @@ import torch
 from PIL import Image
 import requests
 
-url_image_1 = "https://github.com/cvg/LightGlue/blob/main/assets/sacre_coeur1.jpg?raw=true"
+url_image_1 = "https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/assets/phototourism_sample_images/london_bridge_19481797_2295892421.jpg?raw=true"
 image_1 = Image.open(requests.get(url_image_1, stream=True).raw)
-url_image_2 = "https://github.com/cvg/LightGlue/blob/main/assets/sacre_coeur2.jpg?raw=true"
+url_image_2 = "https://github.com/magicleap/SuperGluePretrainedNetwork/blob/master/assets/phototourism_sample_images/london_bridge_19481797_2295892421.jpg?raw=true"
 image_2 = Image.open(requests.get(url_image_2, stream=True).raw)
 
 images = [image_1, image_2]
@@ -156,14 +156,19 @@ image1_indices = torch.nonzero(image1_mask).squeeze()
 image1_keypoints = outputs.keypoints[0, 1][image0_matches]
 
 # Draw matches
-for (keypoint0, keypoint1, score) in zip(image0_keypoints, image1_keypoints, image0_matching_scores):
-    keypoint0_x, keypoint0_y = int(keypoint0[0].item()), int(keypoint0[1].item())
-    keypoint1_x, keypoint1_y = int(keypoint1[0].item() + width), int(keypoint1[1].item())
-    color = tuple([int(score.item() * 255)] * 3)
-    matched_image = cv2.line(matched_image, (keypoint0_x, keypoint0_y), (keypoint1_x, keypoint1_y), color)
-cv2.imwrite(f"matched_image.png", matched_image)
+for keypoint0, keypoint1, score in zip(image0_keypoints, image1_keypoints, image0_matching_scores):
+    keypoint0_x, keypoint0_y = int(keypoint0[0]), int(keypoint0[1])
+    keypoint1_x, keypoint1_y = int(keypoint1[0] + width), int(keypoint1[1])
+    color = [0, 1, 0, 0.5]  # Set color based on score
+    plt.plot([keypoint0_x, keypoint1_x], [keypoint0_y, keypoint1_y], color=color, linewidth=1)
+
+# Save the image
+plt.savefig("matched_image.png", dpi=300, bbox_inches='tight')
+plt.close()
 ```
 
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/632885ba1558dac67c440aa8/PiLL7svnN2dTqOxrsobJb.png)
+
 
 ## Training Details