code

scripts/welspun_classifier.py

@@ -238,7 +238,7 @@ class Welspun_Classifier(ModelWrapper):
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
-        elif a == 1 and max(x) > 0.95:
+        elif a == 2 and max(x) > 0.95:
             resized_frame = cv2.resize(frame, (64, 64))
             cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
                         color=(0, 0, 255),
@@ -250,21 +250,33 @@ class Welspun_Classifier(ModelWrapper):
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
-        else:
-            logger.info("enter else loop")
-            if sum(sum(sum(frame))) == 0:
-                pass
-            else:
+        elif a == 1 and max(x) > 0.95:
             resized_frame = cv2.resize(frame, (64, 64))
-                cv2.putText(frame, text="No Defect", org=(50, 50),
+            cv2.putText(frame, text="Short Tile Defect Detected", org=(50, 50),
                         color=(0, 0, 255),
                         thickness=2,
                         fontScale=1, fontFace=cv2.LINE_AA)
-
             if self.counter % 25 == 0:
-                    self.send_payload("No Defect", resized_frame, "No Defect ", "#044b04", "#24dc24", "sound_1")
+
+                self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[1]), "#472020", "#ed2020",
+                                  "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
+        # else:
+        #     logger.info("enter else loop")
+        #     if sum(sum(sum(frame))) == 0:
+        #         pass
+        #     else:
+        #         resized_frame = cv2.resize(frame, (64, 64))
+        #         cv2.putText(frame, text="No Defect", org=(50, 50),
+        #                     color=(0, 0, 255),
+        #                     thickness=2,
+        #                     fontScale=1, fontFace=cv2.LINE_AA)
+        #
+        #         if self.counter % 25 == 0:
+        #             self.send_payload("No Defect", resized_frame, "No Defect ", "#044b04", "#24dc24", "sound_1")
+        #             logger.info(f"Probability: {prob}")
+        #             self.counter = 0
         # if prob[0] > 0.9:
         #     # print("prob--->",prob[0])
         #     cv2.putText(frame, text="Stitch Detected with Probability :" + str(prob[0]), org=(50, 50),