fix : load model test

image_ref/config.py

@@ -7,17 +7,17 @@ def load_args_contrastive():
     parser.add_argument('--epoches', type=int, default=0)
     parser.add_argument('--save_inter', type=int, default=50)
     parser.add_argument('--eval_inter', type=int, default=1)
-    parser.add_argument('--noise_threshold', type=int, default=0)
+    parser.add_argument('--noise_threshold', type=int, default=500)
     parser.add_argument('--lr', type=float, default=0.001)
-    parser.add_argument('--batch_size', type=int, default=16)
+    parser.add_argument('--batch_size', type=int, default=64)
     parser.add_argument('--positive_prop', type=int, default=None)
     parser.add_argument('--model', type=str, default='ResNet18')
-    parser.add_argument('--dataset_train_dir', type=str, default='../data/processed_data/npy_image/data_training_contrastive')
-    parser.add_argument('--dataset_val_dir', type=str, default='../data/processed_data/npy_image/data_test_contrastive')
-    parser.add_argument('--dataset_ref_dir', type=str, default='../image_ref/img_ref')
-    parser.add_argument('--output', type=str, default='../output/out_contrastive.csv')
-    parser.add_argument('--save_path', type=str, default='../output/best_model_constrastive.pt')
-    parser.add_argument('--pretrain_path', type=str, default='../saved_model/baseline_resnet18_contrastive_prop_30.pt')
+    parser.add_argument('--dataset_train_dir', type=str, default='data/processed_data/npy_image/data_training_contrastive')
+    parser.add_argument('--dataset_val_dir', type=str, default='data/processed_data/npy_image/data_test_contrastive')
+    parser.add_argument('--dataset_ref_dir', type=str, default='image_ref/img_ref')
+    parser.add_argument('--output', type=str, default='output/out_contrastive.csv')
+    parser.add_argument('--save_path', type=str, default='output/best_model_constrastive.pt')
+    parser.add_argument('--pretrain_path', type=str, default='saved_model/baseline_resnet18_contrastive_prop_30_bis.pt')
     args = parser.parse_args()
 
     return args
\ No newline at end of file

image_ref/grad_cam.py

@@ -26,8 +26,8 @@ def compute_class_activation_map():
     path_aer ='../data/processed_data/npy_image/data_test_contrastive/Citrobacter freundii/CITFRE17_AER.npy'
     path_ana ='../data/processed_data/npy_image/data_test_contrastive/Citrobacter freundii/CITFRE17_ANA.npy'
     # path_ref ='../image_ref/img_ref/Citrobacter freundii.npy' #positive
-    path_ref = '../image_ref/img_ref/Enterobacter hormaechei.npy' #negative
-    # path_ref = '../image_ref/img_ref/Proteus mirabilis.npy'  # negative
+    # path_ref = '../image_ref/img_ref/Enterobacter hormaechei.npy' #negative
+    path_ref = '../image_ref/img_ref/Proteus mirabilis.npy'  # negative
     tensor_aer = npy_loader(path_aer)
     tensor_ana = npy_loader(path_ana)
     tensor_ref = npy_loader(path_ref)

image_ref/main.py

@@ -81,7 +81,7 @@ def run_duo(args):
     model.double()
     #load weight
     if args.pretrain_path is not None :
-        'Model weight loaded'
+        print('Model weight loaded')
         load_model(model,args.pretrain_path)
     #move parameters to GPU
     if torch.cuda.is_available():
@@ -168,7 +168,6 @@ def make_prediction_duo(model, data, f_name, f_name2):
             img_ref = img_ref.cuda()
             label = label.cuda()
         output = model(imaer,imana,img_ref)
-        print(output)
         confidence = soft_max(output)
         confidence_pred_list[specie].append(confidence[:,0].data.cpu().numpy())
         #Mono class output (only most postive paire)
@@ -213,4 +212,5 @@ def load_model(model, path):
 
 if __name__ == '__main__':
     args = load_args_contrastive()
+    print(args)
     run_duo(args)
\ No newline at end of file