seg optimizer

demo.py

@@ -12,7 +12,7 @@ import torch
 from utilsK.masterUtils import get_needed_objectsIndex
 def river_demo():
     ##预先设置的参数
-    device_='1'  ##选定模型，可选 cpu,'0','1'
+    device_='0'  ##选定模型，可选 cpu,'0','1'
      
     ##以下参数目前不可改
     #Detweights = "../AIlib/weights/yolov5/class5/best_5classes.pt" 
@@ -66,12 +66,13 @@ def river_demo():
     for i in range(len(folders)):
         imgpath = os.path.join(impth, folders[i])
         im0s=[cv2.imread(imgpath)]
+        H,W,C = im0s[0].shape
         time00 = time.time()
         p_result,timeOut = AI_process(im0s,model,segmodel,names,label_arraylist,rainbows,half,device,conf_thres, iou_thres,allowedList,font=digitFont)
         time11 = time.time()
         image_array = p_result[1]
         cv2.imwrite(  os.path.join( outpth,folders[i] ) ,image_array )
-        print('----AIprocess:%s, %.1f, %s'%(folders[i], (time11 - time00) * 1000,timeOut))
+        print('%s,%d*%d,AI-process: %.1f, %s'%(folders[i],H,W, (time11 - time00) * 1000,timeOut))
         
     
 def road_forest_demo(business ):
@@ -135,6 +136,7 @@ def road_forest_demo(business ):
     impth = 'images/%s/'%(business)
     outpth = 'images/results/'
     folders = os.listdir(impth)
+    folders.sort()
     for i in range(len(folders)):
     #for i in range(2):
         imgpath = os.path.join(impth, folders[i])