.idea/PFCFuse.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
+    <orderEntry type="jdk" jdkName="Remote Python 3.8.10 (sftp://star@192.168.50.108:22/home/star/anaconda3/envs/pfcfuse/bin/python)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="PyDocumentationSettings">

.idea/misc.xml

@@ -12,5 +12,5 @@
       </MavenGeneralSettings>
     </option>
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (pfcfuse)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Remote Python 3.8.10 (sftp://star@192.168.50.108:22/home/star/anaconda3/envs/pfcfuse/bin/python)" project-jdk-type="Python SDK" />
 </project>

test_IVF.py

@@ -17,16 +17,14 @@ current_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
 
 
 os.environ["CUDA_VISIBLE_DEVICES"] = "0"
-pth_path = "whaiFusion11-17-20-18"
+ckpt_path= r"/home/star/whaiDir/PFCFuse/models/whaiFusion11-17-10-34.pth"
-ckpt_path= r"/home/star/whaiDir/PFCFuse/models/"+pth_path+".pth"
-print("path_pth:{}".format(ckpt_path))
 
 for dataset_name in ["sar"]:
     print("\n"*2+"="*80)
-    model_name=pth_path
+    model_name="PFCFuse Enhance  增加widthblock"
     print("The test result of "+dataset_name+' :')
     test_folder = os.path.join('test_img', dataset_name)
-    test_out_folder=os.path.join('test_result',pth_path,dataset_name)
+    test_out_folder=os.path.join('test_result',current_time,dataset_name)
 
     device = 'cuda' if torch.cuda.is_available() else 'cpu'
     Encoder = nn.DataParallel(Restormer_Encoder()).to(device)

train.py

@@ -259,7 +259,5 @@ if True:
         'BaseFuseLayer': BaseFuseLayer.state_dict(),
         'DetailFuseLayer': DetailFuseLayer.state_dict(),
     }
-    savepth = os.path.join("models/whaiFusion" + timestamp + '.pth');
+    torch.save(checkpoint, os.path.join("models/whaiFusion"+timestamp+'.pth'))
-    torch.save(checkpoint, savepth)
-    print("save model:{}".format(savepth))