deephome adaptation

projects/CO-DETR/configs/codino/co_dino_5scale_r50_lsj_8xb2_1x_coco.py

@@ -6,7 +6,7 @@
 # model settings
 num_dec_layer = 6
 loss_lambda = 2.0
-num_classes = 80
+num_classes = 151
 
 image_size = (1024, 1024)
 batch_augments = [

projects/CO-DETR/configs/codino/co_dino_5scale_swin_l_16xb1_16e_o365tococo.py

@@ -1,7 +1,7 @@
 _base_ = ['co_dino_5scale_r50_8xb2_1x_coco.py']
 
 pretrained = 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_large_patch4_window12_384_22k.pth'  # noqa
-load_from = 'https://download.openmmlab.com/mmdetection/v3.0/codetr/co_dino_5scale_swin_large_22e_o365-0a33e247.pth'  # noqa
+load_from = 'https://download.openmmlab.com/mmdetection/v3.0/codetr/co_dino_5scale_swin_large_16e_o365tococo-614254c9.pth'  # noqa
 
 # model settings
 model = dict(

projects/CO-DETR/configs/codino/co_dino_5scale_swin_l_16xb1_16e_o365tococo_deephome.py

@@ -0,0 +1,29 @@
+_base_ = ['co_dino_5scale_swin_l_16xb1_16e_o365tococo.py']
+
+# Modify dataset related settings
+data_root = '/media/deephome/data/'
+metainfo = {
+    'classes': [str(i) for i in range(151)],
+    'palette': [(i, i, i) for i in range(151)],
+}
+
+train_dataloader = dict(
+    batch_size=1,
+    dataset=dict(
+        data_root=data_root,
+        metainfo=metainfo,
+        ann_file='deephome_train_labels.json',
+        data_prefix=dict(img='train_images/')))
+val_dataloader = dict(
+    dataset=dict(
+        data_root=data_root,
+        metainfo=metainfo,
+        ann_file='deephome_train_labels.json',
+        data_prefix=dict(img='train_images/')))
+test_dataloader = val_dataloader
+
+# Modify metric related settings
+val_evaluator = dict(ann_file=data_root + 'deephome_train_labels.json')
+test_evaluator = val_evaluator
+
+train_cfg = dict(val_interval=999)  # No Validation