Dev (#41)

* update: ci

* update: download model from HF

* update: ci

* del: sgmnet

* update: submodule sgmnet

* update: ci

* Remove submodule

* update: ci

* update: submodule darkfeat

* update: submodule lanet

.github/workflows/ci.yml

@@ -0,0 +1,32 @@
+name: CI_CPU
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+      with:
+        submodules: recursive
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: "3.10"
+
+    - name: Install dependencies
+      run: |
+        pip install -r env-docker.txt
+        sudo apt-get update && sudo apt-get install ffmpeg libsm6 libxext6 -y
+
+    - name: Run tests
+      run: python test_app_cli.py

.gitmodules

@@ -25,12 +25,6 @@
 [submodule "third_party/LightGlue"]
 	path = third_party/LightGlue
 	url = https://github.com/cvg/LightGlue.git
-[submodule "third_party/SGMNet"]
-	path = third_party/SGMNet
-	url = https://github.com/vdvchen/SGMNet.git
-[submodule "third_party/DarkFeat"]
-	path = third_party/DarkFeat
-	url = https://github.com/THU-LYJ-Lab/DarkFeat.git
 [submodule "third_party/DeDoDe"]
 	path = third_party/DeDoDe
 	url = https://github.com/Parskatt/DeDoDe.git
@@ -64,3 +58,9 @@
 [submodule "third_party/pram"]
 	path = third_party/pram
 	url = https://github.com/feixue94/pram.git
+[submodule "third_party/SGMNet"]
+	path = third_party/SGMNet
+	url = https://github.com/agipro/SGMNet.git
+[submodule "third_party/DarkFeat"]
+	path = third_party/DarkFeat
+	url = https://github.com/agipro/DarkFeat.git

README.md

@@ -107,6 +107,7 @@ I provide an example to add local feature in [hloc/extractors/example.py](hloc/e
 
 External contributions are very much welcome. Please follow the [PEP8 style guidelines](https://www.python.org/dev/peps/pep-0008/) using a linter like flake8 (reformat using command `python -m black .`). This is a non-exhaustive list of features that might be valuable additions:
 
+- [x] add [CPU CI](.github/workflows/ci.yml)
 - [x] add webcam support
 - [x] add [line feature matching](https://github.com/Vincentqyw/LineSegmentsDetection) algorithms
 - [x] example to add a new feature extractor / matcher

activate.sh

@@ -0,0 +1,6 @@
+# download submodules
+git submodule update --init --recursive
+
+# configuration envs
+pip install -r env-docker.txt
+sudo apt-get update && sudo apt-get install ffmpeg libsm6 libxext6 -y

common/config.yaml

@@ -30,6 +30,7 @@ matcher_zoo:
   DUSt3R:
     # TODO: duster is under development  
     enable: true
+    skip_ci: true
     matcher: duster
     dense: true
     info:
@@ -41,6 +42,7 @@ matcher_zoo:
       display: true
   GIM(dkm):
     enable: true
+    skip_ci: true
     matcher: gim(dkm)
     dense: true
     info:
@@ -52,6 +54,7 @@ matcher_zoo:
       display: true
   RoMa:
     matcher: roma
+    skip_ci: true
     dense: true
     info:
       name: RoMa #dispaly name
@@ -62,6 +65,7 @@ matcher_zoo:
       display: true
   dkm:
     matcher: dkm
+    skip_ci: true
     dense: true
     info:
       name: DKM #dispaly name
@@ -82,6 +86,7 @@ matcher_zoo:
       display: true
   cotr:
     enable: false
+    skip_ci: true
     matcher: cotr
     dense: true
     info:
@@ -368,6 +373,7 @@ matcher_zoo:
     matcher: imp
     feature: sfd2
     dense: false
+    skip_ci: true
     info:
       name: SFD2+IMP #dispaly name
       source: "CVPR 2023"
@@ -380,6 +386,7 @@ matcher_zoo:
     matcher: NN-mutual
     feature: sfd2
     dense: false
+    skip_ci: true
     info:
       name: SFD2+MNN #dispaly name
       source: "CVPR 2023"

env-docker.txt

@@ -30,4 +30,8 @@ torchmetrics==0.6.0
 torchvision==0.17.1
 tqdm==4.65.0
 yacs==0.1.8
-onnxruntime
+onnxruntime
+poselib
+roma
+huggingface_hub
+psutil

hloc/__init__.py

@@ -1,5 +1,6 @@
 import logging
 from packaging import version
+import torch
 
 __version__ = "1.3"
 
@@ -30,4 +31,4 @@
             minimal_version,
             found_version,
         )
-checkpoints_hub = "https://huggingface.co/spaces/Realcat/image-matching-webui/resolve/main/third_party"
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

hloc/extractors/d2net.py

@@ -11,6 +11,7 @@
 from lib.model_test import D2Net as _D2Net
 from lib.pyramid import process_multiscale
 
+
 class D2Net(BaseModel):
     default_conf = {
         "model_name": "d2_tf.pth",
@@ -61,4 +62,4 @@ def _forward(self, data):
             "keypoints": torch.from_numpy(keypoints)[None],
             "scores": torch.from_numpy(scores)[None],
             "descriptors": torch.from_numpy(descriptors.T)[None],
-        }
+        }

hloc/extractors/darkfeat.py

@@ -1,6 +1,7 @@
 import sys
 from pathlib import Path
 import subprocess
+from huggingface_hub import hf_hub_download
 from ..utils.base_model import BaseModel
 from hloc import logger
 
@@ -25,24 +26,14 @@ class DarkFeat(BaseModel):
     def _init(self, conf):
         model_path = darkfeat_path / "checkpoints" / conf["model_name"]
         link = self.weight_urls[conf["model_name"]]
-        if not model_path.exists():
-            model_path.parent.mkdir(exist_ok=True)
-            cmd_wo_proxy = ["gdown", link, "-O", str(model_path)]
-            cmd = ["gdown", link, "-O", str(model_path), "--proxy", self.proxy]
-            logger.info(
-                f"Downloading the DarkFeat model with `{cmd_wo_proxy}`."
-            )
-            try:
-                subprocess.run(cmd_wo_proxy, check=True)
-            except subprocess.CalledProcessError as e:
-                logger.info(f"Downloading the DarkFeat model with `{cmd}`.")
-                try:
-                    subprocess.run(cmd, check=True)
-                except subprocess.CalledProcessError as e:
-                    logger.error(f"Failed to download the DarkFeat model.")
-                    raise e
 
-        self.net = DarkFeat_(model_path)
+        cached_file = hf_hub_download(
+            repo_type="space",
+            repo_id="Realcat/image-matching-webui",
+            filename="third_party/DarkFeat/checkpoints/DarkFeat.pth",
+        )
+
+        self.net = DarkFeat_(cached_file)
         logger.info(f"Load DarkFeat model done.")
 
     def _forward(self, data):

hloc/extractors/lanet.py

@@ -2,12 +2,13 @@
 from pathlib import Path
 import torch
 import subprocess
-from hloc import logger, checkpoints_hub
+from huggingface_hub import hf_hub_download
 from ..utils.base_model import BaseModel
-
+from hloc import logger
 lib_path = Path(__file__).parent / "../../third_party"
 sys.path.append(str(lib_path))
 from lanet.network_v0.model import PointModel
+
 lanet_path = Path(__file__).parent / "../../third_party/lanet"
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -27,16 +28,16 @@ def _init(self, conf):
         )
         if not model_path.exists():
             logger.warning(f"No model found at {model_path}, start downloading")
-            model_link = "{}/lanet/checkpoints/{}".format(
-                checkpoints_hub, f'PointModel_{conf["model_name"]}.pth'
-            )
             model_path.parent.mkdir(exist_ok=True)
-            cmd = [
-                "wget",
-                model_link,
-                "-O",
-                str(model_path),
-            ]
+            cached_file = hf_hub_download(
+                repo_type="space",
+                repo_id="Realcat/image-matching-webui",
+                filename="third_party/lanet/checkpoints/PointModel_{}.pth".format(
+                    conf["model_name"]
+                ),
+            )
+            cmd = ["cp", str(cached_file), str(model_path.parent)]
+            logger.info(f"copy model file `{cmd}`.")
             subprocess.run(cmd, check=True)
 
         self.net = PointModel(is_test=True)

hloc/extractors/r2d2.py

@@ -1,7 +1,7 @@
 import sys
 from pathlib import Path
 import torchvision.transforms as tvf
-
+from hloc import logger
 from ..utils.base_model import BaseModel
 
 r2d2_path = Path(__file__).parent / "../../third_party/r2d2"

hloc/extractors/rord.py

@@ -2,6 +2,7 @@
 from pathlib import Path
 import subprocess
 import torch
+from huggingface_hub import hf_hub_download
 
 from ..utils.base_model import BaseModel
 from hloc import logger
@@ -29,20 +30,23 @@ class RoRD(BaseModel):
     def _init(self, conf):
         model_path = conf["checkpoint_dir"] / conf["model_name"]
         link = self.weight_urls[conf["model_name"]]
+
         if not model_path.exists():
             model_path.parent.mkdir(exist_ok=True)
-            cmd_wo_proxy = ["gdown", link, "-O", str(model_path)]
-            cmd = ["gdown", link, "-O", str(model_path), "--proxy", self.proxy]
-            logger.info(f"Downloading the RoRD model with `{cmd_wo_proxy}`.")
-            try:
-                subprocess.run(cmd_wo_proxy, check=True)
-            except subprocess.CalledProcessError as e:
-                logger.info(f"Downloading the RoRD model with `{cmd}`.")
-                try:
-                    subprocess.run(cmd, check=True)
-                except subprocess.CalledProcessError as e:
-                    logger.error(f"Failed to download the RoRD model.")
-                    raise e
+            cached_file_0 = hf_hub_download(
+                repo_type="space",
+                repo_id="Realcat/image-matching-webui",
+                filename="third_party/RoRD/models/d2net.pth",
+            )
+            cached_file_1 = hf_hub_download(
+                repo_type="space",
+                repo_id="Realcat/image-matching-webui",
+                filename="third_party/RoRD/models/rord.pth",
+            )
+
+            subprocess.run(["cp", cached_file_0, model_path], check=True)
+            subprocess.run(["cp", cached_file_1, model_path], check=True)
+
         self.net = _RoRD(
             model_file=model_path, use_relu=conf["use_relu"], use_cuda=False
         )

hloc/extractors/sfd2.py

@@ -17,9 +17,8 @@
 class SFD2(BaseModel):
     default_conf = {
         "max_keypoints": 4096,
-        "model_name": 'sfd2_20230511_210205_resnet4x.79.pth',
+        "model_name": "sfd2_20230511_210205_resnet4x.79.pth",
         "conf_th": 0.001,
-
     }
     required_inputs = ["image"]
 
@@ -28,13 +27,15 @@ def _init(self, conf):
         self.norm_rgb = tvf.Normalize(
             mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
         )
-        model_fn = pram_path / 'weights' / self.conf['model_name']
+        model_fn = pram_path / "weights" / self.conf["model_name"]
         self.net = load_sfd2(weight_path=model_fn).cuda().eval()
 
         logger.info(f"Load SFD2 model done.")
 
     def _forward(self, data):
-        pred = self.net.extract_local_global(data={'image': self.norm_rgb(data['image'])}, config=self.conf)
+        pred = self.net.extract_local_global(
+            data={"image": self.norm_rgb(data["image"])}, config=self.conf
+        )
         out = {
             "keypoints": pred["keypoints"][0][None],
             "scores": pred["scores"][0][None],

hloc/matchers/aspanformer.py

@@ -4,6 +4,7 @@
 from ..utils import do_system
 from pathlib import Path
 import subprocess
+from huggingface_hub import hf_hub_download
 
 from .. import logger
 
@@ -37,37 +38,20 @@ def _init(self, conf):
         )
         # Download the model.
         if not model_path.exists():
-            # model_path.parent.mkdir(exist_ok=True)
-            tar_path = aspanformer_path / conf["model_name"]
-            if not tar_path.exists():
-                link = self.aspanformer_models[conf["model_name"]]
-                cmd = [
-                    "gdown",
-                    link,
-                    "-O",
-                    str(tar_path),
-                    "--proxy",
-                    self.proxy,
-                ]
-                cmd_wo_proxy = ["gdown", link, "-O", str(tar_path)]
-                logger.info(
-                    f"Downloading the Aspanformer model with `{cmd_wo_proxy}`."
-                )
-                try:
-                    subprocess.run(cmd_wo_proxy, check=True)
-                except subprocess.CalledProcessError as e:
-                    logger.info(
-                        f"Downloading the Aspanformer model with `{cmd}`."
-                    )
-                    try:
-                        subprocess.run(cmd, check=True)
-                    except subprocess.CalledProcessError as e:
-                        logger.error(
-                            f"Failed to download the Aspanformer model."
-                        )
-                        raise e
-
-            do_system(f"cd {str(aspanformer_path)} & tar -xvf {str(tar_path)}")
+            cached_file = hf_hub_download(
+                repo_type="space",
+                repo_id="Realcat/image-matching-webui",
+                filename="third_party/ASpanFormer/weights_aspanformer.tar",
+            )
+            cmd = [
+                "tar",
+                "-xvf",
+                str(cached_file),
+                "-C",
+                str(aspanformer_path / "weights"),
+            ]
+            logger.info(f"Unzip model file `{cmd}`.")
+            subprocess.run(cmd, check=True)
 
         config = get_cfg_defaults()
         config.merge_from_file(conf["config_path"])