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Welspun-Classification
Commit ae9d1080 authored by dasharatha.vamshi's avatar dasharatha.vamshi
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parent 12189ac4
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scripts/welspun_classifier.py
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...@@ -209,148 +209,146 @@ class Welspun_Classifier(ModelWrapper): ...@@ -209,148 +209,146 @@ class Welspun_Classifier(ModelWrapper):
# log.info("Batch size is {}".format(n)) # log.info("Batch size is {}".format(n))
# #
# log.info("Starting inference in synchronous mode") # log.info("Starting inference in synchronous mode")
if self.counter % 3 == 0: start = time.time()
start = time.time() res = self.exec_net.infer(inputs={self.input_blob: images})
res = self.exec_net.infer(inputs={self.input_blob: images}) print(f"Inference time: {time.time() - start}")
print(f"Inference time: {time.time() - start}") # Processing output blob
# Processing output blob # log.info("Processing output blob")
# log.info("Processing output blob") res = res[self.out_blob]
res = res[self.out_blob]
prob = self.softmax_function(res[0]) prob = self.softmax_function(res[0])
x = [] x = []
x.append(prob[0]) x.append(prob[0])
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]) 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 == 1 and x[1] > 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),
thickness=2, thickness=2,
fontScale=1, fontFace=cv2.LINE_AA) fontScale=1, fontFace=cv2.LINE_AA)
# pass # pass
else: else:
self.defect_type = 'Mix' self.defect_type = 'Mix'
resized_frame = cv2.resize(frame, (64, 64)) resized_frame = cv2.resize(frame, (64, 64))
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),
thickness=2, thickness=2,
fontScale=1, fontFace=cv2.LINE_AA) fontScale=1, fontFace=cv2.LINE_AA)
self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020", self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
"#ed2020", "#ed2020",
"sound_1") "sound_1")
logger.info(f"Probability: {prob}") logger.info(f"Probability: {prob}")
# if self.counter % 25 == 0:
# self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
# "#ed2020",
# "sound_1")
# logger.info(f"Probability: {prob}")
# self.counter = 0
elif a == 3 and x[3] > 0.95:
if self.defect_type == 'Short':
cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
# pass
else:
self.defect_type = 'Short'
resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[2]), "#472020",
"#ed2020",
"sound_1")
logger.info(f"Probability: {prob}")
# if self.counter % 25 == 0: # if self.counter % 25 == 0:
# self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[2]), "#472020", # self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
# "#ed2020", # "#ed2020",
# "sound_1") # "sound_1")
# logger.info(f"Probability: {prob}") # logger.info(f"Probability: {prob}")
# self.counter = 0 # self.counter = 0
elif a == 4 and x[4] > 0.95: elif a == 3 and x[3] > 0.95:
if self.defect_type == 'Split': if self.defect_type == 'Short':
cv2.putText(frame, text="Split Defect Detected", org=(50, 50), cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
color=(0, 0, 255), color=(0, 0, 255),
thickness=2, thickness=2,
fontScale=1, fontFace=cv2.LINE_AA) fontScale=1, fontFace=cv2.LINE_AA)
# pass # pass
else: else:
self.defect_type = 'Split' self.defect_type = 'Short'
resized_frame = cv2.resize(frame, (64, 64)) resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Split Defect Detected", org=(50, 50), cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
color=(0, 0, 255), color=(0, 0, 255),
thickness=2, thickness=2,
fontScale=1, fontFace=cv2.LINE_AA) fontScale=1, fontFace=cv2.LINE_AA)
self.send_payload("Split Defect Detected", resized_frame, "Split " + str(prob[3]), "#472020", "#ed2020", self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[2]), "#472020",
"sound_1") "#ed2020",
logger.info(f"Probability: {prob}") "sound_1")
# if self.counter % 25 == 0: logger.info(f"Probability: {prob}")
# self.send_payload("Split Defect Detected", resized_frame, "Split " + str(prob[3]), "#472020", "#ed2020", # if self.counter % 25 == 0:
# "sound_1") # self.send_payload("Short Tile Detected", resized_frame, "Short Tile " + str(prob[2]), "#472020",
# logger.info(f"Probability: {prob}") # "#ed2020",
# self.counter = 0 # "sound_1")
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]), "#044b04", "#24dc24",
"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:
pass
# 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),
# color=(255, 255, 255),
# thickness=1,
# fontScale=1, fontFace=cv2.LINE_AA)
# self.send_payload("Stitch Detected", frame, "Stitch " + str(prob[0]), "#472020", "#ed2020", "sound_1")
# logger.info(f"Probability: {prob}") # logger.info(f"Probability: {prob}")
self.counter = self.counter + 1 # self.counter = 0
print("total time taken to process-------------> ", str(time.time() - starttime)) elif a == 4 and x[4] > 0.95:
# logger.info(f"total time taken to process----------------- {time.time()-starttime}") if self.defect_type == 'Split':
# cv2.imshow('res', frame) cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
else: color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
# pass
else:
self.defect_type = 'Split'
resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
self.send_payload("Split Defect Detected", resized_frame, "Split " + 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 == 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]), "#044b04", "#24dc24",
"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:
pass pass
# 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),
# color=(255, 255, 255),
# thickness=1,
# fontScale=1, fontFace=cv2.LINE_AA)
# self.send_payload("Stitch Detected", frame, "Stitch " + str(prob[0]), "#472020", "#ed2020", "sound_1")
# logger.info(f"Probability: {prob}")
# self.counter= self.counter + 1
print("total time taken to process-------------> ", str(time.time() - starttime))
# logger.info(f"total time taken to process----------------- {time.time()-starttime}")
# cv2.imshow('res', frame)
return frame return frame
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