codes_recognizer/rocognizer.py

@@ -1,7 +1,7 @@
 import cv2
 import torch
-from nn_model import Net
 from torchvision.transforms import transforms
+from codes_recognizer.network_model import Net
 
 
 def recognizer(path):
@@ -14,9 +14,8 @@ def recognizer(path):
 
     # load nn model
     model = Net()
-    model.load_state_dict(torch.load('model.pt'))
+    model.load_state_dict(torch.load('codes_recognizer/model.pt'))
     model.eval()
-
     img = cv2.imread(path)
 
     img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

main.py

@@ -76,11 +76,14 @@ def run():
             '''
             # list [x, y]
             dest_shelf = new_product.shelf()
-            dest_field = board[dest_shelf[0], dest_shelf[1]]
+            dest_field = board[dest_shelf[0]][dest_shelf[1]]
             path = functions.a_star(board[agent.y][agent.x], dest_field, board)
 
             ''''''
             agent.item = new_product
+            path.pop(len(path) - 1)
+            next_step = path.pop(len(path) - 1)
+            agent.is_busy = True
 
 
         if next_step is not None:

product.py

@@ -32,4 +32,5 @@ class FinalProduct:
         self.img = create_image(self)
 
     def shelf(self):
+        print(self.img)
         return assigning(self.img);