add codespell and fix typos discovered by codespell

.github/workflows/pylint.yml

@@ -20,10 +20,11 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install flake8 yapf isort
+        pip install codespell flake8 isort yapf
 
     - name: Lint
       run: |
+        codespell
         flake8 .
         isort --check-only --diff facexlib/ inference/ scripts/ setup.py
         yapf -r -d facexlib/ inference/ scripts/ setup.py

.pre-commit-config.yaml

@@ -24,6 +24,12 @@ repos:
     hooks:
       - id: yapf
 
+  # codespell
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.1.0
+    hooks:
+      - id: codespell
+
   # pre-commit-hooks
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v3.2.0

facexlib/detection/retinaface.py

@@ -84,7 +84,7 @@ def __init__(self, network_name='resnet50', half=False, phase='test'):
         self.target_size, self.max_size = 1600, 2150
         self.resize, self.scale, self.scale1 = 1., None, None
         self.mean_tensor = torch.tensor([[[[104.]], [[117.]], [[123.]]]]).to(device)
-        self.refrence = get_reference_facial_points(default_square=True)
+        self.reference = get_reference_facial_points(default_square=True)
         # Build network.
         backbone = None
         if cfg['name'] == 'mobilenet0.25':
@@ -245,7 +245,7 @@ def __align_multi(self, image, boxes, landmarks, limit=None):
         for landmark in landmarks:
             facial5points = [[landmark[2 * j], landmark[2 * j + 1]] for j in range(5)]
 
-            warped_face = warp_and_crop_face(np.array(image), facial5points, self.refrence, crop_size=(112, 112))
+            warped_face = warp_and_crop_face(np.array(image), facial5points, self.reference, crop_size=(112, 112))
             faces.append(warped_face)
 
         return np.concatenate((boxes, landmarks), axis=1), faces

facexlib/detection/retinaface_utils.py

@@ -163,16 +163,16 @@ def match(threshold, truths, priors, variances, labels, landms, loc_t, conf_t, l
     overlap, encode the bounding boxes, then return the matched indices
     corresponding to both confidence and location preds.
     Args:
-        threshold: (float) The overlap threshold used when mathing boxes.
+        threshold: (float) The overlap threshold used when matching boxes.
         truths: (tensor) Ground truth boxes, Shape: [num_obj, 4].
         priors: (tensor) Prior boxes from priorbox layers, Shape: [n_priors,4].
         variances: (tensor) Variances corresponding to each prior coord,
             Shape: [num_priors, 4].
         labels: (tensor) All the class labels for the image, Shape: [num_obj].
         landms: (tensor) Ground truth landms, Shape [num_obj, 10].
-        loc_t: (tensor) Tensor to be filled w/ endcoded location targets.
+        loc_t: (tensor) Tensor to be filled w/ encoded location targets.
         conf_t: (tensor) Tensor to be filled w/ matched indices for conf preds.
-        landm_t: (tensor) Tensor to be filled w/ endcoded landm targets.
+        landm_t: (tensor) Tensor to be filled w/ encoded landm targets.
         idx: (int) current batch index
     Return:
         The matched indices corresponding to 1)location 2)confidence

facexlib/tracking/kalman_tracker.py

@@ -42,7 +42,7 @@ def __init__(self, bbox):
         # define constant velocity model
         # TODO: x: what is the meanning of x[4:7], v?
         self.kf = KalmanFilter(dim_x=7, dim_z=4)
-        # F (dim_x, dim_x): state transistion matrix
+        # F (dim_x, dim_x): state transition matrix
         self.kf.F = np.array([[1, 0, 0, 0, 1, 0, 0], [0, 1, 0, 0, 0, 1, 0], [0, 0, 1, 0, 0, 0,
                                                                              1], [0, 0, 0, 1, 0, 0, 0],
                               [0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1]])

facexlib/utils/misc.py

@@ -87,7 +87,7 @@ def scandir(dir_path, suffix=None, recursive=False, full_path=False):
         full_path (bool, optional): If set to True, include the dir_path.
             Default: False.
     Returns:
-        A generator for all the interested files with relative pathes.
+        A generator for all the interested files with relative paths.
     """
 
     if (suffix is not None) and not isinstance(suffix, (str, tuple)):

setup.cfg

@@ -20,3 +20,8 @@ known_first_party = facexlib
 known_third_party = PIL,cv2,filterpy,numba,numpy,scipy,torch,torchvision,tqdm
 no_lines_before = STDLIB,LOCALFOLDER
 default_section = THIRDPARTY
+
+[codespell]
+skip = .git,./docs/build
+count =
+quiet-level = 3