video

scripts/welspun_classifier.py

@@ -99,7 +99,7 @@ class Welspun_Classifier(ModelWrapper):
         try:
             frame = obj['frame']
 
-            orig_image = cv2.resize(frame, (224, 224))
+            orig_image = cv2.resize(frame, (3840, 2160))
             frame = self.process_frame(orig_image)
 
             obj['frame'] = cv2.resize(frame, (self.config.get('FRAME_WIDTH'), self.config.get('FRAME_HEIGHT')))
@@ -225,7 +225,7 @@ class Welspun_Classifier(ModelWrapper):
         # if self.counter%1 == 0:
         self.counter = self.counter + 1
 
-        if a == 0 and max(x) > 0.95:
+        if a == 0 and max(x) > 0:
             resized_frame = cv2.resize(frame, (64, 64))
             cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50),
                         color=(0, 0, 255),
@@ -238,7 +238,7 @@ class Welspun_Classifier(ModelWrapper):
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
-        elif a == 2 and max(x) > 0.95:
+        elif a == 2 and max(x) > 0:
             resized_frame = cv2.resize(frame, (64, 64))
             cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
                         color=(0, 0, 255),
@@ -250,7 +250,7 @@ class Welspun_Classifier(ModelWrapper):
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
-        elif a == 1 and max(x) > 0.95:
+        elif a == 1 and max(x) > 0:
             resized_frame = cv2.resize(frame, (64, 64))
             cv2.putText(frame, text="Short Tile Defect Detected", org=(50, 50),
                         color=(0, 0, 255),