Merge pull request #797 from will-jl944/develop_jf

Add HRNet backbone for FasterRCNN

dygraph/PaddleDetection

@@ -1 +1 @@
-Subproject commit 57e9f917dd8191834bcfc98a5df239d7fb42c941
+Subproject commit 66d7eefab9aca8243ddf49a52b748b786b80ffb5

dygraph/paddlex/cv/models/detector.py

@@ -220,7 +220,7 @@ class BaseDetector(BaseModel):
                 pretrain_weights = det_pretrain_weights_dict['_'.join(
                     [self.model_name, self.backbone_name])][0]
                 logging.warning("Pretrain_weights is forcibly set to '{}'. "
-                                "If don't want to use pretrain weights, "
+                                "If you don't want to use pretrain weights, "
                                 "set pretrain_weights to be None.".format(
                                     pretrain_weights))
         pretrained_dir = osp.join(save_dir, 'pretrain')
@@ -699,14 +699,22 @@ class FasterRCNN(BaseDetector):
         self.init_params = locals()
         if backbone not in [
                 'ResNet50', 'ResNet50_vd', 'ResNet50_vd_ssld', 'ResNet34',
-                'ResNet34_vd', 'ResNet101', 'ResNet101_vd'
+                'ResNet34_vd', 'ResNet101', 'ResNet101_vd', 'HRNet_W18'
         ]:
             raise ValueError(
                 "backbone: {} is not supported. Please choose one of "
                 "('ResNet50', 'ResNet50_vd', 'ResNet50_vd_ssld', 'ResNet34', 'ResNet34_vd', "
-                "'ResNet101', 'ResNet101_vd')".format(backbone))
-        self.backbone_name = backbone + '_fpn' if with_fpn else backbone
-        if backbone == 'ResNet50_vd_ssld':
+                "'ResNet101', 'ResNet101_vd', 'HRNet_W18')".format(backbone))
+        self.backbone_name = backbone
+        if backbone == 'HRNet_W18':
+            if not with_fpn:
+                logging.warning(
+                    "Backbone {} should be used along with fpn enabled, 'with_fpn' is forcibly set to True".
+                    format(backbone))
+                with_fpn = True
+            backbone = self._get_backbone(
+                'HRNet', width=18, freeze_at=0, return_idx=[0, 1, 2, 3])
+        elif backbone == 'ResNet50_vd_ssld':
             if not with_fpn:
                 logging.warning(
                     "Backbone {} should be used along with fpn enabled, 'with_fpn' is forcibly set to True".
@@ -769,10 +777,23 @@ class FasterRCNN(BaseDetector):
         rpn_in_channel = backbone.out_shape[0].channels
 
         if with_fpn:
-            neck = ppdet.modeling.FPN(
-                in_channels=[i.channels for i in backbone.out_shape],
-                out_channel=fpn_num_channels,
-                spatial_scales=[1.0 / i.stride for i in backbone.out_shape])
+            self.backbone_name = self.backbone_name + '_fpn'
+
+            if 'HRNet' in self.backbone_name:
+                neck = ppdet.modeling.HRFPN(
+                    in_channels=[i.channels for i in backbone.out_shape],
+                    out_channel=fpn_num_channels,
+                    spatial_scales=[
+                        1.0 / i.stride for i in backbone.out_shape
+                    ],
+                    share_conv=False)
+            else:
+                neck = ppdet.modeling.FPN(
+                    in_channels=[i.channels for i in backbone.out_shape],
+                    out_channel=fpn_num_channels,
+                    spatial_scales=[
+                        1.0 / i.stride for i in backbone.out_shape
+                    ])
             rpn_in_channel = neck.out_shape[0].channels
             anchor_generator_cfg = {
                 'aspect_ratios': aspect_ratios,

dygraph/paddlex/utils/checkpoint.py

@@ -43,6 +43,7 @@ det_pretrain_weights_dict = {
     'FasterRCNN_ResNet101_fpn': ['COCO', 'IMAGENET'],
     'FasterRCNN_ResNet101_vd_fpn': ['COCO', 'IMAGENET'],
     'FasterRCNN_ResNet50_vd_ssld_fpn': ['COCO', 'IMAGENET'],
+    'FasterRCNN_HRNet_W18_fpn': ['COCO', 'IMAGENET'],
     'PPYOLO_ResNet50_vd_dcn': ['COCO', 'IMAGENET'],
     'PPYOLO_ResNet18_vd': ['COCO', 'IMAGENET'],
     'PPYOLO_MobileNetV3_large': ['COCO', 'IMAGENET'],
@@ -212,6 +213,8 @@ imagenet_weights = {
     'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams',
     'FasterRCNN_ResNet101_vd_fpn_IMAGENET':
     'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams',
+    'FasterRCNN_HRNet_W18_fpn_IMAGENET':
+    'https://paddledet.bj.bcebos.com/models/pretrained/HRNet_W18_C_pretrained.pdparams',
     'YOLOv3_ResNet50_vd_dcn_IMAGENET':
     'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams',
     'YOLOv3_ResNet34_IMAGENET':
@@ -304,6 +307,8 @@ coco_weights = {
     'https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams',
     'FasterRCNN_ResNet101_vd_fpn_COCO':
     'https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams',
+    'FasterRCNN_HRNet_W18_fpn_COCO':
+    'https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams',
     'PPYOLO_ResNet50_vd_dcn_COCO':
     'https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams',
     'PPYOLO_ResNet18_vd_COCO':