update

config/data_config/dataset_config.py

@@ -37,6 +37,13 @@ dataset_cfg = {
                         'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'),
     },
 
+    'widerface':{
+        'data_name': 'WiderFace',
+        'num_classes': 1,
+        'class_indexs': [0],
+        'class_names': ('face',),
+    },
+
     'crowdhuman':{
         'data_name': 'CrowdHuman',
         'num_classes': 1,

config/model_config/ctrnet_config.py

@@ -2,17 +2,18 @@
 
 
 ctrnet_cfg = {
-    'ctrnet_n':{
+    'ctrnet_s':{
         # ---------------- Model config ----------------
         ## Backbone
         'bk_pretrained': True,
-        'bk_pretrained_mae': True,
+        'bk_pretrained_mae': False,
         'bk_act': 'silu',
         'bk_norm': 'BN',
         'bk_depthwise': False,
-        'width': 0.25,
+        'width': 0.50,
         'depth': 0.34,
         'ratio': 2.0,
+        'stride': 32,
         'max_stride': 32,
         'out_stride': 4,
         ## Neck
@@ -35,8 +36,8 @@ ctrnet_cfg = {
         'head_depthwise': False,  
         # ---------------- Train config ----------------
         ## input
-        'multi_scale': [0.5, 1.25],   # 320 -> 800
-        'trans_type': 'yolox_n',
+        'multi_scale': [0.5, 1.0],   # 320 -> 640
+        'trans_type': 'yolov5_s',
         # ---------------- Assignment config ----------------
         ## Matcher
         'matcher': "aligned_simota",

models/detectors/ctrnet/ctrnet_basic.py

@@ -136,20 +136,17 @@ class DeformableConv(nn.Module):
         self.reset_parameters()
         self._init_weight()
 
-
     def reset_parameters(self):
         n = self.in_dim * (self.kernel_size**2)
         stdv = 1. / math.sqrt(n)
         self.weight.data.uniform_(-stdv, stdv)
         self.bias.data.zero_()
 
-
     def _init_weight(self):
         # init offset_mask conv
         nn.init.constant_(self.conv_offset_mask.weight, 0.)
         nn.init.constant_(self.conv_offset_mask.bias, 0.)
 
-
     def forward(self, x):
         out = self.conv_offset_mask(x)
         o1, o2, mask = torch.chunk(out, 3, dim=1)

models/detectors/ctrnet/ctrnet_decoder.py

@@ -1,7 +1,7 @@
 import math
 import torch.nn as nn
 
-from .ctrnet_basic import DeConv, RTCBlock
+from .ctrnet_basic import DeConv, DeformableConv
 
 
 def build_decoder(cfg, in_dim, out_dim):
@@ -36,7 +36,7 @@ class CTRDecoder(nn.Module):
         layers = []
         for i in range(self.num_layers):
             layer = nn.Sequential(
-                RTCBlock(in_dim, out_dim[i], 3, False, act_type, norm_type, depthwise),
+                DeformableConv(in_dim, out_dim[i], kernel_size=3, padding=1, stride=1),
                 DeConv(out_dim[i], out_dim[i], kernel_size=4, stride=2, act_type=act_type, norm_type=norm_type)
             )
             layers.append(layer)

models/detectors/rtcdet/rtcdet_backbone.py

@@ -150,7 +150,7 @@ def load_pretrained_weight(model, model_name):
                     checkpoint_state_dict.pop(k)
             else:
                 checkpoint_state_dict.pop(k)
-                print(k)
+                print('Unused key: ', k)
         # load the weight
         model.load_state_dict(checkpoint_state_dict)
     else:

models/detectors/yolov2/yolov2_backbone.py

@@ -114,7 +114,7 @@ def build_backbone(model_name='darknet19', pretrained=False):
                     checkpoint_state_dict.pop(k)
             else:
                 checkpoint_state_dict.pop(k)
-                print(k)
+                print('Unused key: ', k)
 
         model.load_state_dict(checkpoint_state_dict)
 

models/detectors/yolov3/yolov3_backbone.py

@@ -136,7 +136,7 @@ def build_backbone(model_name='darknet53', pretrained=False):
                         checkpoint_state_dict.pop(k)
                 else:
                     checkpoint_state_dict.pop(k)
-                    print(k)
+                    print('Unused key: ', k)
 
             backbone.load_state_dict(checkpoint_state_dict)
         else:

models/detectors/yolov4/yolov4_backbone.py

@@ -135,7 +135,7 @@ def build_backbone(model_name='cspdarknet53', pretrained=False):
                         checkpoint_state_dict.pop(k)
                 else:
                     checkpoint_state_dict.pop(k)
-                    print(k)
+                    print('Unused key: ', k)
 
             backbone.load_state_dict(checkpoint_state_dict)
         else:

models/detectors/yolov5/yolov5_backbone.py

@@ -111,7 +111,7 @@ def load_weight(model, model_name):
                     checkpoint_state_dict.pop(k)
             else:
                 checkpoint_state_dict.pop(k)
-                print(k)
+                print('Unused key: ', k)
 
         model.load_state_dict(checkpoint_state_dict)
     else:

models/detectors/yolov7/yolov7_backbone.py

@@ -195,7 +195,7 @@ def build_backbone(cfg, pretrained=False):
                         checkpoint_state_dict.pop(k)
                 else:
                     checkpoint_state_dict.pop(k)
-                    print(k)
+                    print('Unused key: ', k)
 
             backbone.load_state_dict(checkpoint_state_dict)
         else:

models/detectors/yolox/yolox_backbone.py

@@ -111,7 +111,7 @@ def load_weight(model, model_name):
                     checkpoint_state_dict.pop(k)
             else:
                 checkpoint_state_dict.pop(k)
-                print(k)
+                print('Unused key: ', k)
 
         model.load_state_dict(checkpoint_state_dict)
     else: