good sample to no defect

scripts/welspun_classifier.py

@@ -99,7 +99,7 @@ class Welspun_Classifier(ModelWrapper):
         try:
             frame = obj['frame']
 
-            orig_image = cv2.resize(frame, (3840, 2160))
+            orig_image = cv2.resize(frame, (800, 600))
             frame = self.process_frame(orig_image)
 
             obj['frame'] = cv2.resize(frame, (self.config.get('FRAME_WIDTH'), self.config.get('FRAME_HEIGHT')))
@@ -190,7 +190,7 @@ class Welspun_Classifier(ModelWrapper):
     def process_frame(self, frame):
         starttime = time.time()
         vino_frame = frame.copy()
-
+        vino_frame = vino_frame[20:600,150:650]
         images = np.ndarray(shape=(self.n, self.c, self.h, self.w))
         images_hw = []
         for i in range(self.n):
@@ -232,7 +232,6 @@ class Welspun_Classifier(ModelWrapper):
                         thickness=2,
                         fontScale=1, fontFace=cv2.LINE_AA)
             if self.counter % 25 == 0:
-
                 self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
                                   "#ed2020",
                                   "sound_1")
@@ -245,23 +244,25 @@ class Welspun_Classifier(ModelWrapper):
                         thickness=2,
                         fontScale=1, fontFace=cv2.LINE_AA)
             if self.counter % 25 == 0:
-
-                self.send_payload("Split Detected", resized_frame, "Split " + str(prob[1]), "#472020", "#ed2020",
+                self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[2]), "#472020",
+                                  "#ed2020",
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
-        elif a == 1 and x[1] > 0.95:
+        elif a == 3 and x[3] > 0.95:
             resized_frame = cv2.resize(frame, (64, 64))
-            cv2.putText(frame, text="Short Tile Defect Detected", org=(50, 50),
+            cv2.putText(frame, text="Split 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("Short Tile Detected", resized_frame, "Short Tile " + str(prob[1]), "#472020", "#ed2020",
+                self.send_payload("Split Defect Detected", resized_frame, "Split " + str(prob[3]), "#472020", "#ed2020",
                                   "sound_1")
                 logger.info(f"Probability: {prob}")
                 self.counter = 0
+        elif a == 2:
+            pass
+
         # else:
         #     logger.info("enter else loop")
         #     if sum(sum(sum(frame))) == 0: