update: gim roma

README.md

@@ -217,4 +217,4 @@ This code is built based on [Hierarchical-Localization](https://github.com/cvg/H
 [stars-shield]: https://img.shields.io/github/stars/Vincentqyw/image-matching-webui.svg?style=for-the-badge
 [stars-url]: https://github.com/Vincentqyw/image-matching-webui/stargazers
 [issues-shield]: https://img.shields.io/github/issues/Vincentqyw/image-matching-webui.svg?style=for-the-badge
-[issues-url]: https://github.com/Vincentqyw/image-matching-webui/issues
+[issues-url]: https://github.com/Vincentqyw/image-matching-webui/issues

config/config.yaml

@@ -112,9 +112,21 @@ matcher_zoo:
       paper: https://arxiv.org/abs/2312.14132
       project: https://dust3r.europe.naverlabs.com
       display: true
+  GIM(RoMa):
+    matcher: gim_roma
+    skip_ci: true
+    dense: true
+    enable: true
+    info:
+      name: GIM(RoMa) #dispaly name
+      source: "ICLR 2024"
+      github: https://github.com/xuelunshen/gim
+      paper: https://arxiv.org/abs/2402.11095
+      project: https://xuelunshen.com/gim
+      display: true
+      efficiency: low  # low, medium, high
   GIM(dkm):
     enable: true
-    # skip_ci: true
     matcher: gim(dkm)
     dense: true
     info:

imcui/hloc/match_dense.py

@@ -337,6 +337,23 @@ confs = {
             "dfactor": 8,
         },
     },
+    "gim_roma": {
+        "output": "matches-gim_roma",
+        "model": {
+            "name": "roma",
+            "model_name": "gim_roma_100h.ckpt",
+            "max_keypoints": 2000,
+            "match_threshold": 0.2,
+        },
+        "preprocessing": {
+            "grayscale": False,
+            "force_resize": True,
+            "resize_max": 1024,
+            "width": 320,
+            "height": 240,
+            "dfactor": 8,
+        },
+    },
     "rdd_dense": {
         "output": "matches-rdd_dense",
         "model": {

imcui/hloc/matchers/roma.py

@@ -43,6 +43,14 @@ class Roma(BaseModel):
         logger.info("Loading Roma model")
         # load the model
         weights = torch.load(model_path, map_location="cpu")
+
+        if self.conf["model_name"] == "gim_roma_100h.ckpt":
+            if "state_dict" in weights.keys():
+                weights = weights["state_dict"]
+            for k in list(weights.keys()):
+                if k.startswith("model."):
+                    weights[k.replace("model.", "", 1)] = weights.pop(k)
+
         dinov2_weights = torch.load(dinov2_weights, map_location="cpu")
 
         if str(device) == "cpu":