update: wrapper functions

app.py

@@ -298,7 +298,7 @@ def run(config):
                 outputs=[output_wrapped, geometry_result],
             )
 
-    app.launch(share=False)
+    app.queue().launch(share=False)
 
 
 if __name__ == "__main__":

common/utils.py

@@ -458,11 +458,11 @@ matcher_zoo = {
         "config_feature": extract_features.confs["d2net-ss"],
         "dense": False,
     },
-    "d2net-ms": {
-        "config": match_features.confs["NN-mutual"],
-        "config_feature": extract_features.confs["d2net-ms"],
-        "dense": False,
-    },
+    # "d2net-ms": {
+    #     "config": match_features.confs["NN-mutual"],
+    #     "config_feature": extract_features.confs["d2net-ms"],
+    #     "dense": False,
+    # },
     "alike": {
         "config": match_features.confs["NN-mutual"],
         "config_feature": extract_features.confs["alike"],

hloc/extractors/disk.py

@@ -26,7 +26,7 @@ class DISK(BaseModel):
             pad_if_not_divisible=self.conf["pad_if_not_divisible"],
         )
         return {
-            "keypoints": [f.keypoints for f in features],
-            "scores": [f.detection_scores for f in features],
-            "descriptors": [f.descriptors.t() for f in features],
+            "keypoints": [f.keypoints for f in features][0][None],
+            "scores": [f.detection_scores for f in features][0][None],
+            "descriptors": [f.descriptors.t() for f in features][0][None],
         }

hloc/match_features.py

@@ -330,14 +330,20 @@ def match_images(model, feat0, feat1):
         desc0 = desc0.unsqueeze(0)
     if len(desc1.shape) == 2:
         desc1 = desc1.unsqueeze(0)
+
+    if isinstance(feat0["keypoints"], list):
+        feat0["keypoints"] = feat0["keypoints"][0][None]
+    if isinstance(feat1["keypoints"], list):
+        feat1["keypoints"] = feat1["keypoints"][0][None]
+    
     pred = model(
         {
             "image0": feat0["image"],
-            "keypoints0": feat0["keypoints"][0],
+            "keypoints0": feat0["keypoints"],
             "scores0": feat0["scores"][0].unsqueeze(0),
             "descriptors0": desc0,
             "image1": feat1["image"],
-            "keypoints1": feat1["keypoints"][0],
+            "keypoints1": feat1["keypoints"],
             "scores1": feat1["scores"][0].unsqueeze(0),
             "descriptors1": desc1,
         }

hloc/matchers/lightglue.py

@@ -42,12 +42,12 @@ class LightGlue(BaseModel):
         input = {}
         input["image0"] = {
             "image": data["image0"],
-            "keypoints": data["keypoints0"][None],
+            "keypoints": data["keypoints0"],
             "descriptors": data["descriptors0"].permute(0, 2, 1),
         }
         input["image1"] = {
             "image": data["image1"],
-            "keypoints": data["keypoints1"][None],
+            "keypoints": data["keypoints1"],
             "descriptors": data["descriptors1"].permute(0, 2, 1),
         }
         return self.net(input)

hloc/matchers/sgmnet.py

@@ -82,8 +82,8 @@ class SGMNet(BaseModel):
         logger.info(f"Load SGMNet model done.")
 
     def _forward(self, data):
-        x1 = data["keypoints0"]  # N x 2
-        x2 = data["keypoints1"]
+        x1 = data["keypoints0"].squeeze()  # N x 2
+        x2 = data["keypoints1"].squeeze()
         score1 = data["scores0"].reshape(-1, 1)  # N x 1
         score2 = data["scores1"].reshape(-1, 1)
         desc1 = data["descriptors0"].permute(0, 2, 1)  # 1 x N x 128