diff --git a/.gitignore b/.gitignore
index a7c007b13266d2d12f9a222e57d7fc29f8ef06c0..3d268e1a2890738c635e1432fbe447d25a256efb 100644
--- a/.gitignore
+++ b/.gitignore
@@ -18,5 +18,4 @@ gradio_cached_examples
hloc/matchers/quadtree.py
third_party/QuadTreeAttention
desktop.ini
-experiments*
-datasets/wxbs_benchmark
\ No newline at end of file
+experiments*
\ No newline at end of file
diff --git a/common/app_class.py b/common/app_class.py
index 2afc899ab9184effc4a61728db440d00928c59e8..2939ad28d9138265e9decb50ec92f3115c7732b6 100644
--- a/common/app_class.py
+++ b/common/app_class.py
@@ -197,7 +197,7 @@ class ImageMatchingApp:
cache_examples=False,
label=(
"Examples (click one of the images below to Run"
- " Match)"
+ " Match). Thx: WxBS"
),
)
with gr.Accordion("Supported Algorithms", open=False):
diff --git a/common/utils.py b/common/utils.py
index 2e420f6773c4789fb74c3eba0867493df13da22d..b73f38ba8a1fc72326a4b438bbf03d3e579ac0ac 100644
--- a/common/utils.py
+++ b/common/utils.py
@@ -127,16 +127,29 @@ def gen_examples():
random.seed(1)
example_matchers = [
"disk+lightglue",
+ "xfeat(sparse)",
+ "dedode",
"loftr",
"disk",
+ "roma",
"d2net",
+ "aspanformer",
"topicfm",
"superpoint+superglue",
- "disk+dualsoftmax",
- "roma",
+ "superpoint+lightglue",
+ "superpoint+mnn",
+ "disk",
]
- def gen_images_pairs(path: str, count: int = 5):
+ def distribute_elements(A, B):
+ new_B = np.array(B, copy=True).flatten()
+ np.random.shuffle(new_B)
+ new_B = np.resize(new_B, len(A))
+ np.random.shuffle(new_B)
+ return new_B.tolist()
+
+ def gen_images_pairs(count: int = 5):
+ path = str(ROOT / "datasets/sacre_coeur/mapping")
imgs_list = [
os.path.join(path, file)
for file in os.listdir(path)
@@ -146,9 +159,28 @@ def gen_examples():
selected = random.sample(range(len(pairs)), count)
return [pairs[i] for i in selected]
+ def gen_image_pairs_wxbs(count: int = None):
+ prefix = "datasets/wxbs_benchmark/.WxBS/v1.1"
+ wxbs_path = ROOT / prefix
+ pairs = []
+ for catg in os.listdir(wxbs_path):
+ catg_path = wxbs_path / catg
+ if not catg_path.is_dir():
+ continue
+ for scene in os.listdir(catg_path):
+ scene_path = catg_path / scene
+ if not scene_path.is_dir():
+ continue
+ img1_path = scene_path / "01.png"
+ img2_path = scene_path / "02.png"
+ if img1_path.exists() and img2_path.exists():
+ pairs.append([str(img1_path), str(img2_path)])
+ return pairs
+
# image pair path
- path = ROOT / "datasets/sacre_coeur/mapping"
- pairs = gen_images_pairs(str(path), len(example_matchers))
+ pairs = gen_images_pairs()
+ pairs += gen_image_pairs_wxbs()
+
match_setting_threshold = DEFAULT_SETTING_THRESHOLD
match_setting_max_features = DEFAULT_SETTING_MAX_FEATURES
detect_keypoints_threshold = DEFAULT_DEFAULT_KEYPOINT_THRESHOLD
@@ -157,7 +189,8 @@ def gen_examples():
ransac_confidence = DEFAULT_RANSAC_CONFIDENCE
ransac_max_iter = DEFAULT_RANSAC_MAX_ITER
input_lists = []
- for pair, mt in zip(pairs, example_matchers):
+ dist_examples = distribute_elements(pairs, example_matchers)
+ for pair, mt in zip(pairs, dist_examples):
input_lists.append(
[
pair[0],
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diff --git a/datasets/wxbs_benchmark/.EVD/EVD/h/face.txt b/datasets/wxbs_benchmark/.EVD/EVD/h/face.txt
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diff --git a/datasets/wxbs_benchmark/.EVD/EVD/h/fox.txt b/datasets/wxbs_benchmark/.EVD/EVD/h/fox.txt
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diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/README.txt b/datasets/wxbs_benchmark/.WxBS/v1.1/README.txt
new file mode 100644
index 0000000000000000000000000000000000000000..53dcd09cec7657ffb9d25f69b914fd380af76305
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+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/README.txt
@@ -0,0 +1,47 @@
+Welcome to WxBS version 1.1 -- Wide (multiple) Baseline Dataset.
+
+It contains 34 very challenging image pairs with manually annotated ground truth correspondences.
+The images are organized into several categories:
+
+- WGALBS: with Geometric, Appearance and iLlumination changes
+- WGBS: with Geometric (viewpoint) changes
+- WLABS: with iLlumination and Appearance changes. The viewpoint change is present, but not significant
+- WGSBS: with Geometric and Sensor (thermal camera vs visible) changes
+- WGABS: with Geometric and Appearance changes.
+
+Compared to the original dataset from 2015, v.1.1 contains more correspondences, which are also cleaned, and 3 additional image pairs: WGALBS/kyiv_dolltheater, WGALBS/kyiv_dolltheater2, WGBS/kn-church.
+We also provide cross-validation errors for each of the GT correspondences.
+They are estimated in the following way:
+
+- the fundamental matrix F is estimated with OpenCV 8pt algorithm (no RANSAC), using all points, except one.
+F, _ = cv2.findFundamentalMat(corrs_cur[:,:2], corrs_cur[:,2:], cv2.FM_8POINT)
+Then the symmetrical epipolar distance is calculatd on that held-out point. We have used kornia implementation of the symmetrical epipolar distance:
+
+
+From Hartley and Zisserman, symmetric epipolar distance (11.10)
+sed = (x'^T F x) ** 2 / (((Fx)_1**2) + (Fx)_2**2)) + 1/ (((F^Tx')_1**2) + (F^Tx')_2**2))
+
+https://kornia.readthedocs.io/en/latest/geometry.epipolar.html#kornia.geometry.epipolar.symmetrical_epipolar_distance
+
+
+The labeling is done using [pixelstitch](https://pypi.org/project/pixelstitch/)
+
+There are main intended ways of using the dataset.
+a) First, is evaluation of the image matchers, which are estimating fundamental matrix. One calculates reprojection error on the GT correspondences and report mean error, or the percentage of the GT correspondences, which are in agreement with the estimated F. For more details see the paper[1]
+
+b) For the methods like [CoTR](https://arxiv.org/abs/2103.14167), which look for the correspondences in the image 2, given the query point in image 1, one can directly calculate error between returned point and GT correspondence.
+
+
+***
+If you are using this dataset, please cite us:
+
+[1] WxBS: Wide Baseline Stereo Generalizations. D. Mishkin and M. Perdoch and J.Matas and K. Lenc. In Proc BMVC, 2015
+
+@InProceedings{Mishkin2015WXBS,
+ author = {{Mishkin}, D. and {Matas}, J. and {Perdoch}, M. and {Lenc}, K. },
+ booktitle = {Proceedings of the British Machine Vision Conference},
+ publisher = {BMVA},
+ title = "{WxBS: Wide Baseline Stereo Generalizations}",
+ year = 2015,
+ month = sep
+}
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diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/kyiv/crossval_errors.txt b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/kyiv/crossval_errors.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9ad28740ce26bd03baeb9766ce5198e11d65d5a8
--- /dev/null
+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/kyiv/crossval_errors.txt
@@ -0,0 +1,38 @@
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diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/01.png b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/01.png
new file mode 100644
index 0000000000000000000000000000000000000000..c857dacc1a029373e76db064f1d074e80dc03ceb
--- /dev/null
+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/01.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:26c6e49251eeeaeec9290f6df841a7ac912d1051f342c7d4a4c2f5b9a69540e6
+size 599212
diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/02.png b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/02.png
new file mode 100644
index 0000000000000000000000000000000000000000..430c0e076263407c36895282121b585e09d5cd98
--- /dev/null
+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/02.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c2abc34567f59818457ba0c69eef03868b6b0be276c73388bade0fbfff21970
+size 540896
diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/corrs.txt b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/corrs.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8a045058924894eba94c7b02ccf8038a8d67f1ef
--- /dev/null
+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/corrs.txt
@@ -0,0 +1,36 @@
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diff --git a/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/crossval_errors.txt b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/crossval_errors.txt
new file mode 100644
index 0000000000000000000000000000000000000000..aec67f6c0ec471fac7a21dd8402b563e6906ec51
--- /dev/null
+++ b/datasets/wxbs_benchmark/.WxBS/v1.1/WLABS/ministry/crossval_errors.txt
@@ -0,0 +1,36 @@
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diff --git a/datasets/wxbs_benchmark/download.py b/datasets/wxbs_benchmark/download.py
new file mode 100644
index 0000000000000000000000000000000000000000..eaaf6a3ed23dbdd9164386a5a2d81b672acb6398
--- /dev/null
+++ b/datasets/wxbs_benchmark/download.py
@@ -0,0 +1,3 @@
+from wxbs_benchmark.dataset import *
+dset = EVDDataset('.EVD', download=True)
+dset = WxBSDataset('.WxBS', subset='test', download=True)
\ No newline at end of file
diff --git a/datasets/wxbs_benchmark/example.py b/datasets/wxbs_benchmark/example.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bbf13d48b59d549084d342ee4719a5ccdbfd467
--- /dev/null
+++ b/datasets/wxbs_benchmark/example.py
@@ -0,0 +1,21 @@
+import os
+from pathlib import Path
+
+ROOT_PATH = Path("/teamspace/studios/this_studio/image-matching-webui")
+prefix = "datasets/wxbs_benchmark/.WxBS/v1.1"
+wxbs_path = ROOT_PATH / prefix
+
+pairs = []
+for catg in os.listdir(wxbs_path):
+ catg_path = wxbs_path / catg
+ if not catg_path.is_dir():
+ continue
+ for scene in os.listdir(catg_path):
+ scene_path = catg_path / scene
+ if not scene_path.is_dir():
+ continue
+ img1_path = scene_path / "01.png"
+ img2_path = scene_path / "02.png"
+ pairs.append([str(img1_path),str(img2_path)])
+
+breakpoint()
\ No newline at end of file