No-self-use. (open-mmlab#275)

mmpose/core/fp16/hooks.py

@@ -52,15 +52,17 @@ def before_run(self, runner):
         # convert model to fp16
         wrap_fp16_model(runner.model)
 
-    def copy_grads_to_fp32(self, fp16_net, fp32_weights):
+    @staticmethod
+    def copy_grads_to_fp32(fp16_net, fp32_weights):
         """Copy gradients from fp16 model to fp32 weight copy."""
         for fp32_param, fp16_param in zip(fp32_weights, fp16_net.parameters()):
             if fp16_param.grad is not None:
                 if fp32_param.grad is None:
                     fp32_param.grad = fp32_param.data.new(fp32_param.size())
                 fp32_param.grad.copy_(fp16_param.grad)
 
-    def copy_params_to_fp16(self, fp16_net, fp32_weights):
+    @staticmethod
+    def copy_params_to_fp16(fp16_net, fp32_weights):
         """Copy updated params from fp32 weight copy to fp16 model."""
         for fp16_param, fp32_param in zip(fp16_net.parameters(), fp32_weights):
             fp16_param.data.copy_(fp32_param.data)

mmpose/core/post_processing/group.py

@@ -235,7 +235,8 @@ def top_k(self, heatmaps, tags):
 
         return ans
 
-    def adjust(self, ans, heatmaps):
+    @staticmethod
+    def adjust(ans, heatmaps):
         """Adjust the coordinates for better accuracy.
 
         Note:
@@ -271,7 +272,8 @@ def adjust(self, ans, heatmaps):
                                       0:2] = (x + 0.5, y + 0.5)
         return ans
 
-    def refine(self, heatmap, tag, keypoints):
+    @staticmethod
+    def refine(heatmap, tag, keypoints):
         """Given initial keypoint predictions, we identify missing joints.
 
         Note:

mmpose/datasets/datasets/bottom_up/bottom_up_coco.py

@@ -97,7 +97,8 @@ def __init__(self,
 
         print(f'=> num_images: {self.num_images}')
 
-    def _get_mapping_id_name(self, imgs):
+    @staticmethod
+    def _get_mapping_id_name(imgs):
         """
         Args:
             imgs (dict): dict of image info.

mmpose/datasets/datasets/hand/hand_base_dataset.py

@@ -62,7 +62,8 @@ def __init__(self,
 
         self.pipeline = Compose(self.pipeline)
 
-    def _get_mapping_id_name(self, imgs):
+    @staticmethod
+    def _get_mapping_id_name(imgs):
         """
         Args:
             imgs (dict): dict of image info.
@@ -121,7 +122,8 @@ def evaluate(self, cfg, preds, output_dir, *args, **kwargs):
         """Evaluate keypoint results."""
         raise NotImplementedError
 
-    def _write_keypoint_results(self, keypoints, res_file):
+    @staticmethod
+    def _write_keypoint_results(keypoints, res_file):
         """Write results into a json file."""
 
         with open(res_file, 'w') as f:

mmpose/datasets/datasets/hand/interhand2d_dataset.py

@@ -78,7 +78,8 @@ def __init__(self,
         print(f'=> num_images: {self.num_images}')
         print(f'=> load {len(self.db)} samples')
 
-    def _cam2pixel(self, cam_coord, f, c):
+    @staticmethod
+    def _cam2pixel(cam_coord, f, c):
         """Transform the joints from their camera coordinates to their pixel
         coordinates.
 
@@ -101,7 +102,8 @@ def _cam2pixel(self, cam_coord, f, c):
         img_coord = np.concatenate((x[:, None], y[:, None], z[:, None]), 1)
         return img_coord
 
-    def _world2cam(self, world_coord, R, T):
+    @staticmethod
+    def _world2cam(world_coord, R, T):
         """Transform the joints from their world coordinates to their camera
         coordinates.
 

mmpose/datasets/datasets/mesh/mesh_h36m_dataset.py

@@ -52,7 +52,8 @@ def evaluate(self, outputs, res_folder, metric='joint_error', logger=None):
         name_value = OrderedDict(info_str)
         return name_value
 
-    def _write_keypoint_results(self, keypoints, res_file):
+    @staticmethod
+    def _write_keypoint_results(keypoints, res_file):
         """Write results into a json file."""
 
         with open(res_file, 'w') as f:
@@ -87,7 +88,8 @@ def _report_metric(self, res_file):
         info_str.append(('MPJPE-PA', mpjpe_pa * 1000))
         return info_str
 
-    def evaluate_kernel(self, pred_joints_3d, joints_3d, joints_3d_visible):
+    @staticmethod
+    def evaluate_kernel(pred_joints_3d, joints_3d, joints_3d_visible):
         """Evaluate one example."""
         # Only 14 lsp joints are used for evaluation
         joint_mapper = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 18]

mmpose/datasets/datasets/mesh/mosh_dataset.py

@@ -31,7 +31,8 @@ def __init__(self, ann_file, pipeline, test_mode=False):
         self.db = self._get_db(ann_file)
         self.pipeline = Compose(self.pipeline)
 
-    def _get_db(self, ann_file):
+    @staticmethod
+    def _get_db(ann_file):
         """Load dataset."""
         data = np.load(ann_file)
         _betas = data['shape'].astype(np.float32)

mmpose/datasets/datasets/top_down/topdown_coco_dataset.py

@@ -112,7 +112,8 @@ def __init__(self,
         print(f'=> num_images: {self.num_images}')
         print(f'=> load {len(self.db)} samples')
 
-    def _get_mapping_id_name(self, imgs):
+    @staticmethod
+    def _get_mapping_id_name(imgs):
         """
         Args:
             imgs (dict): dict of image info.

mmpose/datasets/datasets/top_down/topdown_coco_wholebody_dataset.py

@@ -125,7 +125,8 @@ def __init__(self,
         print(f'=> num_images: {self.num_images}')
         print(f'=> load {len(self.db)} samples')
 
-    def _make_flip_pairs(self):
+    @staticmethod
+    def _make_flip_pairs():
         body = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14],
                 [15, 16]]
         foot = [[17, 20], [18, 21], [19, 22]]

mmpose/datasets/datasets/top_down/topdown_mpii_trb_dataset.py

@@ -194,7 +194,8 @@ def evaluate(self, outputs, res_folder, metric='PCKh', **kwargs):
 
         return name_value
 
-    def _write_keypoint_results(self, keypoints, res_file):
+    @staticmethod
+    def _write_keypoint_results(keypoints, res_file):
         """Write results into a json file."""
 
         with open(res_file, 'w') as f:

mmpose/datasets/datasets/top_down/topdown_posetrack18_dataset.py

@@ -199,7 +199,8 @@ def evaluate(self, outputs, res_folder, metric='mAP', **kwargs):
 
         return name_value
 
-    def _write_posetrack18_keypoint_results(self, keypoint_results, gt_folder,
+    @staticmethod
+    def _write_posetrack18_keypoint_results(keypoint_results, gt_folder,
                                             pred_folder):
         """Write results into a json file.
 

mmpose/datasets/pipelines/bottom_up_transform.py

@@ -229,7 +229,8 @@ def __init__(self, rot_factor, scale_factor, scale_type, trans_factor):
         self.scale_type = scale_type
         self.trans_factor = trans_factor
 
-    def _get_affine_matrix(self, center, scale, res, rot=0):
+    @staticmethod
+    def _get_affine_matrix(center, scale, res, rot=0):
         """Generate transformation matrix."""
         h = scale
         t = np.zeros((3, 3), dtype=np.float32)
@@ -255,7 +256,8 @@ def _get_affine_matrix(self, center, scale, res, rot=0):
             t = np.dot(t_inv, np.dot(rot_mat, np.dot(t_mat, t)))
         return t
 
-    def _affine_joints(self, joints, mat):
+    @staticmethod
+    def _affine_joints(joints, mat):
         """Affine the joints by the transform matrix."""
         joints = np.array(joints)
         shape = joints.shape

mmpose/models/backbones/hrnet.py

@@ -42,8 +42,8 @@ def __init__(self,
         self.fuse_layers = self._make_fuse_layers()
         self.relu = nn.ReLU(inplace=True)
 
-    def _check_branches(self, num_branches, num_blocks, in_channels,
-                        num_channels):
+    @staticmethod
+    def _check_branches(num_branches, num_blocks, in_channels, num_channels):
         """Check input to avoid ValueError."""
         if num_branches != len(num_blocks):
             error_msg = f'NUM_BRANCHES({num_branches}) ' \

mmpose/models/backbones/regnet.py

@@ -202,8 +202,8 @@ def _make_stem_layer(self, in_channels, base_channels):
         self.add_module(self.norm1_name, norm1)
         self.relu = nn.ReLU(inplace=True)
 
-    def generate_regnet(self,
-                        initial_width,
+    @staticmethod
+    def generate_regnet(initial_width,
                         width_slope,
                         width_parameter,
                         depth,

mmpose/models/keypoint_heads/bottom_up_higher_resolution_head.py

@@ -77,8 +77,9 @@ def __init__(self,
             num_deconv_filters, num_deconv_kernels, num_basic_blocks,
             cat_output)
 
-    def _make_final_layers(self, in_channels, final_layer_output_channels,
-                           extra, num_deconv_layers, num_deconv_filters):
+    @staticmethod
+    def _make_final_layers(in_channels, final_layer_output_channels, extra,
+                           num_deconv_layers, num_deconv_filters):
         """Make final layers."""
         if extra is not None and 'final_conv_kernel' in extra:
             assert extra['final_conv_kernel'] in [1, 3]
@@ -147,7 +148,8 @@ def _make_deconv_layers(self, in_channels, deconv_layer_output_channels,
 
         return nn.ModuleList(deconv_layers)
 
-    def _get_deconv_cfg(self, deconv_kernel):
+    @staticmethod
+    def _get_deconv_cfg(deconv_kernel):
         """Get configurations for deconv layers."""
         if deconv_kernel == 4:
             padding = 1

mmpose/models/keypoint_heads/bottom_up_simple_head.py

@@ -120,7 +120,8 @@ def _make_deconv_layer(self, num_layers, num_filters, num_kernels):
 
         return nn.Sequential(*layers)
 
-    def _get_deconv_cfg(self, deconv_kernel):
+    @staticmethod
+    def _get_deconv_cfg(deconv_kernel):
         """Get configurations for deconv layers."""
         if deconv_kernel == 4:
             padding = 1

mmpose/models/keypoint_heads/top_down_multi_stage_head.py

@@ -139,7 +139,8 @@ def _make_deconv_layer(self, num_layers, num_filters, num_kernels):
 
         return nn.Sequential(*layers)
 
-    def _get_deconv_cfg(self, deconv_kernel):
+    @staticmethod
+    def _get_deconv_cfg(deconv_kernel):
         """Get configurations for deconv layers."""
         if deconv_kernel == 4:
             padding = 1

mmpose/models/keypoint_heads/top_down_simple_head.py

@@ -118,7 +118,8 @@ def _make_deconv_layer(self, num_layers, num_filters, num_kernels):
 
         return nn.Sequential(*layers)
 
-    def _get_deconv_cfg(self, deconv_kernel):
+    @staticmethod
+    def _get_deconv_cfg(deconv_kernel):
         """Get configurations for deconv layers."""
         if deconv_kernel == 4:
             padding = 1

mmpose/models/losses/mesh_loss.py

@@ -282,7 +282,8 @@ def __init__(self,
             raise NotImplementedError(
                 f'GAN type {self.gan_type} is not implemented.')
 
-    def _wgan_loss(self, input, target):
+    @staticmethod
+    def _wgan_loss(input, target):
         """wgan loss.
 
         Args:

mmpose/models/losses/multi_loss_factory.py

@@ -29,7 +29,8 @@ def _make_input(t, requires_grad=False, device=torch.device('cpu')):
 class HeatmapLoss(nn.Module):
     """Accumulate the heatmap loss for each image in the batch."""
 
-    def forward(self, pred, gt, mask):
+    @staticmethod
+    def forward(pred, gt, mask):
         """
         Note:
             batch_size: N