Merge pull request #39 from ternaus/fixes

Fixes

.pre-commit-config.yaml

@@ -10,11 +10,11 @@ repos:
       - id: isort
         args: ["--profile", "black"]
   - repo: https://github.com/psf/black
-    rev: 21.6b0
+    rev: 21.12b0
     hooks:
       - id: black
   - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 4.0.1
     hooks:
       - id: flake8
         language_version: python3

requirements_dev.txt

@@ -1,42 +1,13 @@
-black==21.6b0
-flake8==3.9.2
-flake8-bandit==2.1.2
-flake8-breakpoint==1.1.0
-flake8-bugbear==21.3.1
-flake8-builtins==1.5.3
-flake8-colors==0.1.9
-flake8-comprehensions==3.3.1
-flake8-debugger==4.0.0
-flake8-docstrings==1.5.0
-flake8-eradicate==1.0.0
-flake8-executable==2.1.1
-flake8-fixme==1.1.1
-flake8-graphql==0.2.5
-flake8-implicit-str-concat==0.2.0
-flake8-logging-format==0.6.0
-flake8-mock==0.3
-flake8-pathlib==0.1.3
-flake8-plugin-utils==1.3.1
-flake8-polyfill==1.0.2
-flake8-print==4.0.0
-flake8-printf-formatting==1.1.2
-flake8-pytest==1.3
-flake8-pytest-style==1.3.0
-flake8-raise==0.0.5
-flake8-requests==0.4.0
-flake8-requirements==1.3.3
-flake8-string-format==0.3.0
-flake8-tidy-imports==4.2.1
-flake8-todo==0.7
-flake8-tuple==0.4.1
+black==21.12b0
+flake8==4.0.1
 iglovikov-helper-functions==0.0.53
-isort==5.8.0
-mypy==0.910
+isort==5.10.1
+mypy==0.931
 onnx==1.9.0
 pep8-naming==0.11.1
-pip==21.1.3
-pre-commit==2.13.0
-pylint==2.8.2
+pip==21.3.1
+pre_commit==2.17.0
+pylint==2.12.2
 pytest==6.2.4
 pytest-asyncio==0.15.1
 pytest-clarity==0.3.0a0

retinaface/__init__.py

@@ -1 +1 @@
-__version__ = "0.0.7"
+__version__ = "0.0.8"

retinaface/box_utils.py

@@ -196,7 +196,7 @@ def encode_landm(
     priors = torch.cat([priors_cx, priors_cy, priors_w, priors_h], dim=2)
     g_cxcy = matched[:, :, :2] - priors[:, :, :2]
     # encode variance
-    g_cxcy = g_cxcy // variances[0] * priors[:, :, 2:]
+    g_cxcy /= variances[0] * priors[:, :, 2:]
     # return target for smooth_l1_loss
     return g_cxcy.reshape(g_cxcy.size(0), -1)
 

retinaface/inference.py

@@ -90,9 +90,9 @@ def unnormalize(image: Union[np.ndarray, torch.Tensor]) -> Union[np.ndarray, tor
     std = [0.229, 0.224, 0.225]
 
     for c in range(image.shape[-1]):
-        image[:, :, c] *= std[c]
-        image[:, :, c] += mean[c]
-        image[:, :, c] *= 255
+        image[:, :, c] *= std[c]  # type: ignore
+        image[:, :, c] += mean[c]  # type: ignore
+        image[:, :, c] *= 255  # type: ignore
 
     return image
 

retinaface/predict_single.py

@@ -94,7 +94,7 @@ def predict_jsons(
             landmarks_np = landmarks.cpu().numpy()
             resize_coeff = original_height / transformed_height
 
-            boxes *= resize_coeff
+            boxes_np *= resize_coeff
             landmarks_np = landmarks_np.reshape(-1, 10) * resize_coeff
 
             for box_id, bbox in enumerate(boxes_np):

retinaface/train.py

@@ -49,7 +49,7 @@ def __init__(self, config: Adict[str, Any]) -> None:
 
         self.loss = object_from_dict(self.config.loss, priors=self.prior_box)
 
-    def setup(self, state=0) -> None:  # type: ignore
+    def setup(self, stage=0) -> None:  # type: ignore
         self.preproc = Preproc(img_dim=self.config.image_size[0])
 
     def forward(self, batch: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:  # type: ignore