recognizer.py is returnig list od codess

coder/rocognizer.py

@@ -4,14 +4,22 @@ from nn_model import Net
 from torchvision.transforms import transforms
 
 
-def recognizer(a_path):
+def recognizer(paths):
+
+    codes = []
     code = []
-    path = a_path
 
     transform = transforms.Compose([transforms.ToTensor(),
                                     transforms.Normalize((0.5,), (0.5,)),
                                     ])
 
+    # load nn model
+    model = Net()
+    model.load_state_dict(torch.load('model.pt'))
+    model.eval()
+
+
+    for path in paths:
         img = cv2.imread(path)
 
         img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
@@ -23,11 +31,6 @@ def recognizer(a_path):
 
         rects = [cv2.boundingRect(ctr) for ctr in ctrs]
 
-    # load nn model
-    model = Net()
-    model.load_state_dict(torch.load('model.pt'))
-    model.eval()
-
         for rect in rects:
             # Crop image
             crop_img = img[rect[1]:rect[1] + rect[3] + 10, rect[0]:rect[0] + rect[2] + 10, 0]
@@ -44,11 +47,10 @@ def recognizer(a_path):
             probab = list(ps.numpy()[0])
             code.append(probab.index(max(probab)))
 
-    print(code)
+        codes.append(code)
         # cv2.imshow("Code", img)
         # cv2.waitKey()
-    return code
+
+    return codes
 
 
-recognizer("55555.jpg")
-