update keypoint code citation (#4456)

deploy/python/keypoint_postprocess.py

@@ -23,7 +23,7 @@ from keypoint_preprocess import get_affine_mat_kernel, get_affine_transform
 
 
 class HrHRNetPostProcess(object):
-    '''
+    """
     HrHRNet postprocess contain:
         1) get topk keypoints in the output heatmap
         2) sample the tagmap's value corresponding to each of the topk coordinate
@@ -37,7 +37,7 @@ class HrHRNetPostProcess(object):
 
         inputs(list[heatmap]): the output list of modle, [heatmap, heatmap_maxpool, tagmap], heatmap_maxpool used to get topk
         original_height, original_width (float): the original image size
-    '''
+    """
 
     def __init__(self, max_num_people=30, heat_thresh=0.2, tag_thresh=1.):
         self.max_num_people = max_num_people
@@ -212,7 +212,7 @@ class HRNetPostProcess(object):
         return output_flipped
 
     def get_max_preds(self, heatmaps):
-        '''get predictions from score maps
+        """get predictions from score maps
 
         Args:
             heatmaps: numpy.ndarray([batch_size, num_joints, height, width])
@@ -220,7 +220,7 @@ class HRNetPostProcess(object):
         Returns:
             preds: numpy.ndarray([batch_size, num_joints, 2]), keypoints coords
             maxvals: numpy.ndarray([batch_size, num_joints, 2]), the maximum confidence of the keypoints
-        '''
+        """
         assert isinstance(heatmaps,
                           np.ndarray), 'heatmaps should be numpy.ndarray'
         assert heatmaps.ndim == 4, 'batch_images should be 4-ndim'
@@ -286,6 +286,10 @@ class HRNetPostProcess(object):
         return coord
 
     def dark_postprocess(self, hm, coords, kernelsize):
+        """
+        refer to https://github.com/ilovepose/DarkPose/lib/core/inference.py
+
+        """
         hm = self.gaussian_blur(hm, kernelsize)
         hm = np.maximum(hm, 1e-10)
         hm = np.log(hm)

deploy/python/keypoint_preprocess.py

@@ -11,7 +11,9 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+"""
+this code is based on https://github.com/open-mmlab/mmpose/mmpose/core/post_processing/post_transforms.py
+"""
 import cv2
 import numpy as np
 

deploy/python/preprocess.py

@@ -14,6 +14,7 @@
 
 import cv2
 import numpy as np
+from keypoint_preprocess import get_affine_transform
 
 
 def decode_image(im_file, im_info):
@@ -263,90 +264,6 @@ class WarpAffine(object):
         self.scale = scale
         self.shift = shift
 
-    def _get_3rd_point(self, a, b):
-        assert len(
-            a) == 2, 'input of _get_3rd_point should be point with length of 2'
-        assert len(
-            b) == 2, 'input of _get_3rd_point should be point with length of 2'
-        direction = a - b
-        third_pt = b + np.array([-direction[1], direction[0]], dtype=np.float32)
-        return third_pt
-
-    def rotate_point(self, pt, angle_rad):
-        """Rotate a point by an angle.
-
-        Args:
-        pt (list[float]): 2 dimensional point to be rotated
-        angle_rad (float): rotation angle by radian
-
-        Returns:
-        list[float]: Rotated point.
-        """
-        assert len(pt) == 2
-        sn, cs = np.sin(angle_rad), np.cos(angle_rad)
-        new_x = pt[0] * cs - pt[1] * sn
-        new_y = pt[0] * sn + pt[1] * cs
-        rotated_pt = [new_x, new_y]
-
-        return rotated_pt
-
-    def get_affine_transform(self,
-                             center,
-                             input_size,
-                             rot,
-                             output_size,
-                             shift=(0., 0.),
-                             inv=False):
-        """Get the affine transform matrix, given the center/scale/rot/output_size.
-
-        Args:
-        center (np.ndarray[2, ]): Center of the bounding box (x, y).
-        input_size (np.ndarray[2, ]): Size of input feature (width, height).
-        rot (float): Rotation angle (degree).
-        output_size (np.ndarray[2, ]): Size of the destination heatmaps.
-        shift (0-100%): Shift translation ratio wrt the width/height.
-            Default (0., 0.).
-        inv (bool): Option to inverse the affine transform direction.
-            (inv=False: src->dst or inv=True: dst->src)
-
-        Returns:
-        np.ndarray: The transform matrix.
-        """
-        assert len(center) == 2
-        assert len(output_size) == 2
-        assert len(shift) == 2
-
-        if not isinstance(input_size, (np.ndarray, list)):
-            input_size = np.array([input_size, input_size], dtype=np.float32)
-        scale_tmp = input_size
-
-        shift = np.array(shift)
-        src_w = scale_tmp[0]
-        dst_w = output_size[0]
-        dst_h = output_size[1]
-
-        rot_rad = np.pi * rot / 180
-        src_dir = self.rotate_point([0., src_w * -0.5], rot_rad)
-        dst_dir = np.array([0., dst_w * -0.5])
-
-        src = np.zeros((3, 2), dtype=np.float32)
-
-        src[0, :] = center + scale_tmp * shift
-        src[1, :] = center + src_dir + scale_tmp * shift
-        src[2, :] = self._get_3rd_point(src[0, :], src[1, :])
-
-        dst = np.zeros((3, 2), dtype=np.float32)
-        dst[0, :] = [dst_w * 0.5, dst_h * 0.5]
-        dst[1, :] = np.array([dst_w * 0.5, dst_h * 0.5]) + dst_dir
-        dst[2, :] = self._get_3rd_point(dst[0, :], dst[1, :])
-
-        if inv:
-            trans = cv2.getAffineTransform(np.float32(dst), np.float32(src))
-        else:
-            trans = cv2.getAffineTransform(np.float32(src), np.float32(dst))
-
-        return trans
-
     def __call__(self, im, im_info):
         """
         Args:
@@ -371,7 +288,7 @@ class WarpAffine(object):
             input_h, input_w = self.input_h, self.input_w
             c = np.array([w / 2., h / 2.], dtype=np.float32)
 
-        trans_input = self.get_affine_transform(c, s, 0, [input_w, input_h])
+        trans_input = get_affine_transform(c, s, 0, [input_w, input_h])
         img = cv2.resize(img, (w, h))
         inp = cv2.warpAffine(
             img, trans_input, (input_w, input_h), flags=cv2.INTER_LINEAR)

ppdet/data/source/keypoint_coco.py

@@ -11,7 +11,9 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  
 # See the License for the specific language governing permissions and   
 # limitations under the License.
-
+"""
+this code is base on https://github.com/open-mmlab/mmpose
+"""
 import os
 import cv2
 import numpy as np
@@ -25,8 +27,7 @@ from ppdet.core.workspace import register, serializable
 
 @serializable
 class KeypointBottomUpBaseDataset(DetDataset):
-    """Base class for bottom-up datasets. Adapted from
-        https://github.com/open-mmlab/mmpose
+    """Base class for bottom-up datasets. 
 
     All datasets should subclass it.
     All subclasses should overwrite:
@@ -90,8 +91,7 @@ class KeypointBottomUpBaseDataset(DetDataset):
 @register
 @serializable
 class KeypointBottomUpCocoDataset(KeypointBottomUpBaseDataset):
-    """COCO dataset for bottom-up pose estimation. Adapted from
-        https://github.com/open-mmlab/mmpose
+    """COCO dataset for bottom-up pose estimation. 
 
     The dataset loads raw features and apply specified transforms
     to return a dict containing the image tensors and other information.
@@ -262,8 +262,7 @@ class KeypointBottomUpCocoDataset(KeypointBottomUpBaseDataset):
 @register
 @serializable
 class KeypointBottomUpCrowdPoseDataset(KeypointBottomUpCocoDataset):
-    """CrowdPose dataset for bottom-up pose estimation. Adapted from
-        https://github.com/open-mmlab/mmpose
+    """CrowdPose dataset for bottom-up pose estimation. 
 
     The dataset loads raw features and apply specified transforms
     to return a dict containing the image tensors and other information.
@@ -387,9 +386,7 @@ class KeypointTopDownBaseDataset(DetDataset):
 @register
 @serializable
 class KeypointTopDownCocoDataset(KeypointTopDownBaseDataset):
-    """COCO dataset for top-down pose estimation. Adapted from
-        https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
-        Copyright (c) Microsoft, under the MIT License.
+    """COCO dataset for top-down pose estimation. 
 
     The dataset loads raw features and apply specified transforms
     to return a dict containing the image tensors and other information.
@@ -582,9 +579,7 @@ class KeypointTopDownCocoDataset(KeypointTopDownBaseDataset):
 @register
 @serializable
 class KeypointTopDownMPIIDataset(KeypointTopDownBaseDataset):
-    """MPII dataset for topdown pose estimation. Adapted from
-        https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
-        Copyright (c) Microsoft, under the MIT License.
+    """MPII dataset for topdown pose estimation.
 
     The dataset loads raw features and apply specified transforms
     to return a dict containing the image tensors and other information.

ppdet/data/transform/keypoint_operators.py

@@ -682,6 +682,10 @@ class ToHeatmapsTopDown(object):
         self.sigma = sigma
 
     def __call__(self, records):
+        """refer to
+            https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
+            Copyright (c) Microsoft, under the MIT License.
+        """
         joints = records['joints']
         joints_vis = records['joints_vis']
         num_joints = joints.shape[0]

ppdet/metrics/keypoint_metrics.py

@@ -27,11 +27,10 @@ __all__ = ['KeyPointTopDownCOCOEval', 'KeyPointTopDownMPIIEval']
 
 
 class KeyPointTopDownCOCOEval(object):
-    '''
-    Adapted from
+    """refer to
         https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
         Copyright (c) Microsoft, under the MIT License.
-    '''
+    """
 
     def __init__(self,
                  anno_file,
@@ -286,7 +285,7 @@ class KeyPointTopDownMPIIEval(object):
         return self.eval_results
 
     def evaluate(self, outputs, savepath=None):
-        """Evaluate PCKh for MPII dataset. Adapted from
+        """Evaluate PCKh for MPII dataset. refer to
         https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
         Copyright (c) Microsoft, under the MIT License.
 

ppdet/modeling/keypoint_utils.py

@@ -11,6 +11,9 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+"""
+this code is based on https://github.com/open-mmlab/mmpose
+"""
 
 import cv2
 import numpy as np