From bd68214d45a9505ec392f6c191ddbba37a30e7da Mon Sep 17 00:00:00 2001
From: Mihai Dusmanu <mihai.dusmanu@gmail.com>
Date: Wed, 9 Jun 2021 15:44:29 +0200
Subject: [PATCH 1/2] Added SIFT features using PyCOLMAP.

---
 hloc/extract_features.py | 10 +++++++
 hloc/extractors/sift.py  | 65 ++++++++++++++++++++++++++++++++++++++++
 hloc/match_features.py   |  8 +++++
 3 files changed, 83 insertions(+)
 create mode 100644 hloc/extractors/sift.py

diff --git a/hloc/extract_features.py b/hloc/extract_features.py
index a214a35a..85b22f54 100644
--- a/hloc/extract_features.py
+++ b/hloc/extract_features.py
@@ -74,6 +74,16 @@
             'resize_max': 1600,
         },
     },
+    'sift': {
+        'output': 'feats-sift',
+        'model': {
+            'name': 'sift'
+        },
+        'preprocessing': {
+            'grayscale': True,
+            'resize_max': 1600,
+        },
+    },
     'dir': {
         'output': 'global-feats-dir',
         'model': {
diff --git a/hloc/extractors/sift.py b/hloc/extractors/sift.py
new file mode 100644
index 00000000..55736b14
--- /dev/null
+++ b/hloc/extractors/sift.py
@@ -0,0 +1,65 @@
+import copy
+import numpy as np
+import torch
+
+from ..utils.base_model import BaseModel
+
+import pycolmap
+
+
+EPS = 1e-6
+
+
+def sift_to_rootsift(descs):
+    l1_norm_descs = descs / (np.linalg.norm(descs, ord=1, axis=-1)[:, np.newaxis] + EPS)
+    sqrt_l1_norm_descs = np.sqrt(l1_norm_descs)
+    root_descs = sqrt_l1_norm_descs / (np.linalg.norm(sqrt_l1_norm_descs, axis=-1)[:, np.newaxis] + EPS)
+    return root_descs
+
+
+class SIFT(BaseModel):
+    default_conf = {
+        'num_octaves': 4,
+        'octave_resolution': 3,
+        'first_octave': 0,
+        'edge_thresh': 10,
+        'peak_thresh': 0.01,
+        'upright': False,
+        'root': True,
+        'max_keypoints': -1
+    }
+    required_inputs = ['image']
+
+    def _init(self, conf):
+        self.root = conf['root']
+        self.max_keypoints = conf['max_keypoints']
+
+        vlfeat_conf = copy.deepcopy(conf)
+        vlfeat_conf.pop('name', None)
+        vlfeat_conf.pop('root', None)
+        vlfeat_conf.pop('max_keypoints', None)
+        self.extract = lambda image: pycolmap.extract_sift(
+            image, **vlfeat_conf
+        )
+
+    def _forward(self, data):
+        image = data['image']
+
+        keypoints, scores, descriptors = self.extract(image[0, 0].cpu().numpy())
+        keypoints = keypoints[:, : 2]  # Keep only x, y.
+
+        if self.root:
+            descriptors = sift_to_rootsift(descriptors)
+        
+        if self.max_keypoints != -1:
+            # It is unclear whether scores from PyCOLMAP are 100% correct - follow https://github.com/mihaidusmanu/pycolmap/issues/8.
+            indices = np.argsort(scores)[:: -1][: self.max_keypoints]
+            keypoints = keypoints[indices, :]
+            scores = scores[indices]
+            descriptors = descriptors[indices, :]
+
+        return {
+            'keypoints': torch.from_numpy(keypoints)[None],
+            'scores': torch.from_numpy(scores)[None],
+            'descriptors': torch.from_numpy(descriptors.T)[None],
+        }
diff --git a/hloc/match_features.py b/hloc/match_features.py
index bb0db870..52249b70 100644
--- a/hloc/match_features.py
+++ b/hloc/match_features.py
@@ -33,6 +33,14 @@
             'mutual_check': True,
             'distance_threshold': 0.7,
         },
+    },
+    'NN-ratio': {
+        'output': 'matches-NN-mutual-ratio.8',
+        'model': {
+            'name': 'nearest_neighbor',
+            'mutual_check': True,
+            'ratio_threshold': 0.8,
+        }
     }
 }
 

From d3fa344d786761282676bd629f91b9e985bf27ca Mon Sep 17 00:00:00 2001
From: Mihai Dusmanu <mihai.dusmanu@gmail.com>
Date: Wed, 9 Jun 2021 16:08:42 +0200
Subject: [PATCH 2/2] Added asserts for input image.

---
 hloc/extractors/sift.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/hloc/extractors/sift.py b/hloc/extractors/sift.py
index 55736b14..75cb0b44 100644
--- a/hloc/extractors/sift.py
+++ b/hloc/extractors/sift.py
@@ -44,6 +44,8 @@ def _init(self, conf):
 
     def _forward(self, data):
         image = data['image']
+        assert image.shape[1] == 1
+        assert image.min() >= -EPS and image.max() <= 1 + EPS
 
         keypoints, scores, descriptors = self.extract(image[0, 0].cpu().numpy())
         keypoints = keypoints[:, : 2]  # Keep only x, y.