fix code reference and licence (#4477)

ppdet/modeling/assigners/atss_assigner.py

@@ -79,7 +79,10 @@ class ATSSAssigner(nn.Layer):
                 gt_bboxes,
                 bg_index,
                 gt_scores=None):
-        r"""The assignment is done in following steps
+        r"""This code is based on
+            https://github.com/fcjian/TOOD/blob/master/mmdet/core/bbox/assigners/atss_assigner.py
+
+        The assignment is done in following steps
         1. compute iou between all bbox (bbox of all pyramid levels) and gt
         2. compute center distance between all bbox and gt
         3. on each pyramid level, for each gt, select k bbox whose center

ppdet/modeling/assigners/task_aligned_assigner.py

@@ -47,7 +47,10 @@ class TaskAlignedAssigner(nn.Layer):
                 gt_bboxes,
                 bg_index,
                 gt_scores=None):
-        r"""The assignment is done in following steps
+        r"""This code is based on
+            https://github.com/fcjian/TOOD/blob/master/mmdet/core/bbox/assigners/task_aligned_assigner.py
+
+        The assignment is done in following steps
         1. compute alignment metric between all bbox (bbox of all pyramid levels) and gt
         2. select top-k bbox as candidates for each gt
         3. limit the positive sample's center in gt (because the anchor-free detector

ppdet/modeling/heads/detr_head.py

@@ -28,6 +28,10 @@ __all__ = ['DETRHead', 'DeformableDETRHead']
 
 
 class MLP(nn.Layer):
+    """This code is based on
+        https://github.com/facebookresearch/detr/blob/main/models/detr.py
+    """
+
     def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
         super().__init__()
         self.num_layers = num_layers
@@ -48,7 +52,11 @@ class MLP(nn.Layer):
 
 
 class MultiHeadAttentionMap(nn.Layer):
-    """This is a 2D attention module, which only returns the attention softmax (no multiplication by value)"""
+    """This code is based on
+        https://github.com/facebookresearch/detr/blob/main/models/segmentation.py
+
+        This is a 2D attention module, which only returns the attention softmax (no multiplication by value)
+    """
 
     def __init__(self, query_dim, hidden_dim, num_heads, dropout=0.0,
                  bias=True):
@@ -94,9 +102,11 @@ class MultiHeadAttentionMap(nn.Layer):
 
 
 class MaskHeadFPNConv(nn.Layer):
-    """
-    Simple convolutional head, using group norm.
-    Upsampling is done using a FPN approach
+    """This code is based on
+        https://github.com/facebookresearch/detr/blob/main/models/segmentation.py
+
+        Simple convolutional head, using group norm.
+        Upsampling is done using a FPN approach
     """
 
     def __init__(self, input_dim, fpn_dims, context_dim, num_groups=8):
@@ -307,7 +317,7 @@ class DeformableDETRHead(nn.Layer):
         linear_init_(self.score_head)
         constant_(self.score_head.bias, -4.595)
         constant_(self.bbox_head.layers[-1].weight)
-        
+
         with paddle.no_grad():
             bias = paddle.zeros_like(self.bbox_head.layers[-1].bias)
             bias[2:] = -2.0

ppdet/modeling/heads/tood_head.py

@@ -48,6 +48,10 @@ class ScaleReg(nn.Layer):
 
 
 class TaskDecomposition(nn.Layer):
+    """This code is based on
+        https://github.com/fcjian/TOOD/blob/master/mmdet/models/dense_heads/tood_head.py
+    """
+
     def __init__(
             self,
             feat_channels,
@@ -105,6 +109,9 @@ class TaskDecomposition(nn.Layer):
 
 @register
 class TOODHead(nn.Layer):
+    """This code is based on
+        https://github.com/fcjian/TOOD/blob/master/mmdet/models/dense_heads/tood_head.py
+    """
     __inject__ = ['nms', 'static_assigner', 'assigner']
     __shared__ = ['num_classes']
 

ppdet/modeling/transformers/deformable_transformer.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.
+#
+# Modified from Deformable-DETR (https://github.com/fundamentalvision/Deformable-DETR)
+# Copyright (c) 2020 SenseTime. All Rights Reserved.
 
 from __future__ import absolute_import
 from __future__ import division

ppdet/modeling/transformers/detr_transformer.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.
+#
+# Modified from DETR (https://github.com/facebookresearch/detr)
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 
 from __future__ import absolute_import
 from __future__ import division

ppdet/modeling/transformers/matchers.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.
+#
+# Modified from DETR (https://github.com/facebookresearch/detr)
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 
 from __future__ import absolute_import
 from __future__ import division

ppdet/modeling/transformers/position_encoding.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.
+#
+# Modified from DETR (https://github.com/facebookresearch/detr)
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 
 from __future__ import absolute_import
 from __future__ import division

ppdet/modeling/transformers/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.
+#
+# Modified from DETR (https://github.com/facebookresearch/detr)
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 
 from __future__ import absolute_import
 from __future__ import division