test metaposfix for ISIC20

config/defaults.py

@@ -268,6 +268,7 @@
 
 _C.DATASETS.N_AUG = 1
 
+_C.DATASETS.META_POS = ['anterior torso','head/neck','lower extremity','palms/soles','posterior torso','upper extremity']
 # -----------------------------------------------------------------------------
 # DataLoader
 # -----------------------------------------------------------------------------

configs/effb4_meta_default20_extrameta_w_d_metafix.yaml

@@ -0,0 +1,34 @@
+MODEL:
+
+  BACKBONE: 'effnetb4'
+  NAME: 'effb4_SVMeta'
+
+  IMG_FCS:  [3584,512]
+  META_DIMS: [17,6,1,3,2]
+
+
+DATASETS:
+  ROOT_DIR: ['../data/all18_coloradj','../data/all20_coloradj']
+  DICT_LABEL: ['NV', 'MEL'] 
+  INFO_CSV: ['./dat/all18_info1_convert20.csv','./dat/all20_info1.csv']
+  NUM_CLASS: 2
+  META_POS: [,'head/neck','upper extremity','lower extremity','torso','palms/soles','oral/genital']
+
+
+DATALOADER:
+  BATCH_SIZE: 12
+  SAMPLER: 'weighted_meta'
+  NUM_WORKERS: 8
+TEST:
+  BATCH_SIZE: 32
+
+MISC:
+  OUT_DIR: "../checkpoint/effb4_meta_default20_d_metafix"
+  VALID_EPOCH: 10
+  LOG_PERIOD: 10000
+
+INPUT: 
+  CRP_SCALE: [0.1,1.0]
+  CRP_RATIO: [0.75,1.33]
+SOLVER:
+  EPOCHS: 50

configs/effb4_meta_default20_extrameta_w_d_metafix_test.yaml

@@ -0,0 +1,31 @@
+MODEL:
+
+  BACKBONE: 'effnetb4'
+  NAME: 'effb4_SVMeta'
+
+  IMG_FCS:  [3584,512]
+  META_DIMS: [17,6,1,3,2]
+DATASETS:
+  ROOT_DIR: ['../data/all20_usp_coloradj']
+  DICT_LABEL: ['NV', 'MEL'] 
+  INFO_CSV: ['./dat/all20_info_usp.csv']
+  NUM_CLASS: 2
+  META_POS: [,'head/neck','upper extremity','lower extremity','torso','palms/soles','oral/genital']
+
+DATALOADER:
+  BATCH_SIZE: 12
+  SAMPLER: 'weighted_meta'
+  NUM_WORKERS: 8
+TEST:
+  BATCH_SIZE: 32
+
+MISC:
+  OUT_DIR: "../checkpoint/effb4_meta_default20_d_metafix"
+  VALID_EPOCH: 10
+  LOG_PERIOD: 10000
+
+INPUT: 
+  CRP_SCALE: [0.1,1.0]
+  CRP_RATIO: [0.75,1.33]
+SOLVER:
+  EPOCHS: 50

data/datasets/ISIC_Dataset.py

@@ -75,11 +75,13 @@ def __init__(self, root, meta_list, dict_label = ['MEL', 'NV', 'BCC', 'AKIEC', '
             #self.bbox_info = np.array(im_info[:,7:11]).astype('float32')
 
             meta_feat = list()
+
             if 'age' in meta_list:
                 meta_age = parse_age(im_info[:,4], th_list=np.arange(5,90,5))
                 meta_feat.append(meta_age)
             if 'pos' in meta_list:
-                meta_pos = parse_pos(im_info[:,5], all_pos =['anterior torso','head/neck','lower extremity','palms/soles','posterior torso','upper extremity'])
+                all_pos = self.cfg.DATASETS.META_POS
+                meta_pos = parse_pos(im_info[:,5], all_pos =all_pos)#['anterior torso','head/neck','lower extremity','palms/soles','posterior torso','upper extremity'])
                 meta_feat.append(meta_pos)
             if 'sex' in meta_list:
                 meta_sex = parse_sex(im_info[:,6])

utils/parse_meta.py

@@ -80,6 +80,18 @@ def parse_pos(pos_list, all_pos):
                 # in ISIC19, there are more position ,need fix
                 pos_idx = all_pos.index(pos)    
                 meta_pos[idx][pos_idx] = 1
+            else: # if meta info is a superset of given pos
+                pos_out = []
+                for idx,pp in enumerate(all_pos):
+                    if pp in  pos:
+                        pos_out.append(idx)
+                if len(pos_out)==1:
+                    meta_pos[idx][pos_out[0]] = 1
+                elif len(pos_out)==0:
+                    pass
+                else:
+                    raise ValueError('two match')
+
         elif math.isnan(pos) is True:
             pass
         else: