Update app.py

app.py

@@ -60,6 +60,39 @@ def stitch_images(images):
 
     return composite
 
+def unified_matching_plot2(image0, image1, kpts0, kpts1, mkpts0, mkpts1, color, text, path=None, show_keypoints=False, fast_viz=False, opencv_display=False, opencv_title='matches', small_text=[]):
+    plt.figure(figsize=(15, 15))
+    plt.subplot(1, 2, 1)
+    plt.imshow(image0)
+    plt.scatter(kpts0[:, 0], kpts0[:, 1], color='r', s=1)
+    plt.axis('off')
+
+    plt.subplot(1, 2, 2)
+    plt.imshow(image1)
+    plt.scatter(kpts1[:, 0], kpts1[:, 1], color='r', s=1)
+    plt.axis('off')
+
+    fig, ax = plt.subplots(figsize=(20, 20))
+    plt.plot([mkpts0[:, 0], mkpts1[:, 0] + image0.shape[1]], [mkpts0[:, 1], mkpts1[:, 1]], 'r', lw=0.5)
+    plt.scatter(mkpts0[:, 0], mkpts0[:, 1], s=2, marker='o', color='b')
+    plt.scatter(mkpts1[:, 0] + image0.shape[1], mkpts1[:, 1], s=2, marker='o', color='g')
+    plt.imshow(np.hstack([image0, image1]), aspect='auto')
+
+    plt.suptitle('\n'.join(text), fontsize=20, fontweight='bold')
+    plt.tight_layout()
+    plt.show()
+
+    buf = BytesIO()
+    plt.savefig(buf, format='png')
+    buf.seek(0)
+    img_arr = np.frombuffer(buf.getvalue(), dtype=np.uint8)
+    buf.close()
+    img = cv2.imdecode(img_arr, 1)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    plt.close(fig)
+
+    return img
+
 # Main functions
 def detect_and_crop(target_image, query_image, threshold=0.5, nms_threshold=0.3):
     target_sizes = torch.Tensor([target_image.size[::-1]])