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Welspun-Classification
Commit 525d15c1 authored by dasharatha.vamshi's avatar dasharatha.vamshi
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scripts/model/resnet34-demo.mapping 0 → 100644
View file @ 525d15c1
<?xml version="1.0" ?>
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scripts/model/resnet34-demo.xml 0 → 100644
View file @ 525d15c1
This source diff could not be displayed because it is too large. You can view the blob instead.
scripts/welspun_classifier.py
View file @ 525d15c1
...@@ -43,7 +43,7 @@ class Welspun_Classifier(ModelWrapper): ...@@ -43,7 +43,7 @@ class Welspun_Classifier(ModelWrapper):
# open-vino # open-vino
self.sink_layer = {'0': 'conv2d_58/BiasAdd/Add', '1': 'conv2d_66/BiasAdd/Add', '2': 'conv2d_74/BiasAdd/Add'} self.sink_layer = {'0': 'conv2d_58/BiasAdd/Add', '1': 'conv2d_66/BiasAdd/Add', '2': 'conv2d_74/BiasAdd/Add'}
self.model_detector_pth = os.path.join(self.base_model_path, "resnet34-wel4.xml") self.model_detector_pth = os.path.join(self.base_model_path, "resnet34-demo.xml")
self.model_bin = os.path.splitext(self.model_detector_pth)[0] + ".bin" self.model_bin = os.path.splitext(self.model_detector_pth)[0] + ".bin"
self.ie = IECore() self.ie = IECore()
self.net1 = self.ie.read_network(model=self.model_detector_pth, weights=self.model_bin) self.net1 = self.ie.read_network(model=self.model_detector_pth, weights=self.model_bin)
...@@ -222,12 +222,13 @@ class Welspun_Classifier(ModelWrapper): ...@@ -222,12 +222,13 @@ class Welspun_Classifier(ModelWrapper):
x.append(prob[1]) x.append(prob[1])
x.append(prob[2]) x.append(prob[2])
x.append(prob[3]) x.append(prob[3])
x.append(prob[4])
a = x.index(max(x)) a = x.index(max(x))
# print(type(prob)) # print(type(prob))
# if self.counter%1 == 0: # if self.counter%1 == 0:
self.counter = self.counter + 1 self.counter = self.counter + 1
if a == 0 and x[0] > 0.95: if a == 1 and x[1] > 0.95:
if self.defect_type == 'Mix': if self.defect_type == 'Mix':
cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50), cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50),
color=(0, 0, 255), color=(0, 0, 255),
...@@ -251,7 +252,7 @@ class Welspun_Classifier(ModelWrapper): ...@@ -251,7 +252,7 @@ class Welspun_Classifier(ModelWrapper):
# "sound_1") # "sound_1")
# logger.info(f"Probability: {prob}") # logger.info(f"Probability: {prob}")
# self.counter = 0 # self.counter = 0
elif a == 2 and x[2] > 0.95: elif a == 3 and x[3] > 0.95:
if self.defect_type == 'Short': if self.defect_type == 'Short':
cv2.putText(frame, text="Short Defect Detected", org=(50, 50), cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
color=(0, 0, 255), color=(0, 0, 255),
...@@ -275,7 +276,7 @@ class Welspun_Classifier(ModelWrapper): ...@@ -275,7 +276,7 @@ class Welspun_Classifier(ModelWrapper):
# "sound_1") # "sound_1")
# logger.info(f"Probability: {prob}") # logger.info(f"Probability: {prob}")
# self.counter = 0 # self.counter = 0
elif a == 3 and x[3] > 0.95: elif a == 4 and x[4] > 0.95:
if self.defect_type == 'Split': if self.defect_type == 'Split':
cv2.putText(frame, text="Split Defect Detected", org=(50, 50), cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
color=(0, 0, 255), color=(0, 0, 255),
...@@ -297,6 +298,28 @@ class Welspun_Classifier(ModelWrapper): ...@@ -297,6 +298,28 @@ class Welspun_Classifier(ModelWrapper):
# "sound_1") # "sound_1")
# logger.info(f"Probability: {prob}") # logger.info(f"Probability: {prob}")
# self.counter = 0 # self.counter = 0
elif a == 0 and x[0] > 0.95:
if self.defect_type == 'good':
cv2.putText(frame, text="No Defect", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
# pass
else:
self.defect_type = 'good'
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)
self.send_payload("No Defect", resized_frame, "no defect " + str(prob[3]), "#472020", "#ed2020",
"sound_1")
logger.info(f"Probability: {prob}")
# if self.counter % 25 == 0:
# 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: elif a == 2:
pass pass
......
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