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Welspun-Classification
Commit 1dcd5d75 authored by dasharatha.vamshi's avatar dasharatha.vamshi
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parent a1998435
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Showing with 28 additions and 45 deletions
scripts/welspun_classifier.py
View file @ 1dcd5d75
......@@ -190,7 +190,8 @@ class Welspun_Classifier(ModelWrapper):
def process_frame(self, frame):
starttime = time.time()
vino_frame = frame.copy()
vino_frame = vino_frame[20:600,150:650]
# vino_frame = vino_frame[20:600,150:650]
vino_frame = vino_frame[5: 600, 70: 650]
images = np.ndarray(shape=(self.n, self.c, self.h, self.w))
images_hw = []
for i in range(self.n):
......@@ -234,28 +235,22 @@ class Welspun_Classifier(ModelWrapper):
fontScale=1, fontFace=cv2.LINE_AA)
# pass
else:
# self.defect_type = 'Mix'
self.defect_type = 'Mix'
resized_frame = cv2.resize(frame, (64, 64))
# cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50),
# color=(0, 0, 255),
# thickness=2,
# fontScale=1, fontFace=cv2.LINE_AA)
# self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
# "#ed2020",
# "sound_1")
# logger.info(f"Probability: {prob}")
if self.counter % 25 == 0:
self.defect_type = 'Mix'
resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
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
cv2.putText(frame, text="Mix Color Defect Detected", org=(50, 50),
color=(0, 0, 255),
thickness=2,
fontScale=1, fontFace=cv2.LINE_AA)
self.send_payload("Mix Color Detected", resized_frame, "Mix Color " + str(prob[0]), "#472020",
"#ed2020",
"sound_1")
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 == 2 and x[2] > 0.95:
if self.defect_type == 'Short':
cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
......@@ -264,17 +259,6 @@ class Welspun_Classifier(ModelWrapper):
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:
self.defect_type = 'Short'
resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Short Defect Detected", org=(50, 50),
......@@ -285,7 +269,12 @@ class Welspun_Classifier(ModelWrapper):
"#ed2020",
"sound_1")
logger.info(f"Probability: {prob}")
self.counter = 0
# if self.counter % 25 == 0:
# 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 == 3 and x[3] > 0.95:
if self.defect_type == 'Split':
cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
......@@ -294,16 +283,6 @@ class Welspun_Classifier(ModelWrapper):
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.defect_type = 'Split'
resized_frame = cv2.resize(frame, (64, 64))
cv2.putText(frame, text="Split Defect Detected", org=(50, 50),
......@@ -313,7 +292,11 @@ class Welspun_Classifier(ModelWrapper):
self.send_payload("Split Defect Detected", resized_frame, "Split " + str(prob[3]), "#472020", "#ed2020",
"sound_1")
logger.info(f"Probability: {prob}")
self.counter = 0
# 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
......
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