def draw_objs(self, img, is_id=False, is_rect=True, is_tag=True):
for obj in self.tracker.get_objs():
font = cv2.FONT_HERSHEY_SIMPLEX
font_scale = 0.3
thickness = 1
x1, y1, x2, y2, oid = obj
x1 = int(x1)
y1 = int(y1)
x2 = int(x2)
y2 = int(y2)
oid = int(oid)
rectangle_color = (255, 255, 255)
text_color = (0, 0, 0)
tag = self.detected[oid]["tag"]
if tag == "Bottle - NG":
rectangle_color = (0, 0, 255)
text_color = (255, 255, 255)
if is_id:
# img = cv2.putText(img, str(oid), (x, y), font, font_scale,
# (0, 255, 255), thickness)
img = draw_label(img, str(oid), (x1, y1))
if is_tag:
score = self.detected[oid]["score"]
text = tag + " ( " + str(int(1000 * score) / 10) + "% )"
img = draw_label(img, text, (x1, max(y1, 15)), rectangle_color,
text_color)
if is_rect:
img = cv2.rectangle(img, (x1, max(y1, 15)), (x2, y2),
rectangle_color, thickness)
# img = cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 255),
# thickness)
return img
def draw_objs(self, img, is_id=False, is_rect=True, is_tag=True):
for obj in self.tracker.get_objs():
font = cv2.FONT_HERSHEY_SIMPLEX
font_scale = 0.3
thickness = 1
x1, y1, x2, y2, oid = obj
x1 = int(x1)
y1 = int(y1)
x2 = int(x2)
y2 = int(y2)
oid = int(oid)
if is_id:
#img = cv2.putText(img, str(oid), (x, y), font, font_scale,
# (0, 255, 255), thickness)
img = draw_label(img, str(oid), (x1, y1))
if is_tag:
tag = self.detected[oid]['tag']
score = self.detected[oid]['score']
text = tag + ' ( ' + str(int(1000 * score) / 10) + '% )'
img = draw_label(img, text, (x1, max(y1, 15)))
if is_rect:
img = cv2.rectangle(img, (x1, max(y1, 15)), (x2, y2),
(255, 255, 255), thickness)
#img = cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 255),
# thickness)
return img
def draw_confidence_level(img, prediction):
height, width = img.shape[0], img.shape[1]
font = cv2.FONT_HERSHEY_DUPLEX
font_scale = 0.7
thickness = 1
prob_str = str(int(prediction['probability']*1000)/10)
prob_str = ' (' + prob_str + '%)'
(x1, y1), (x2, y2) = parse_bbox(prediction, width, height)
text = prediction['tagName'] + prob_str
img = draw_label(img, text, (x1, max(y1, 15)))
return img
def draw_confidence_level(img, prediction):
height, width = img.shape[0], img.shape[1]
# font = cv2.FONT_HERSHEY_DUPLEX
# font_scale = 0.5
# thickness = 1
prob_str = str(int(prediction["probability"] * 1000) / 10)
prob_str = " (" + prob_str + "%)"
(x1, y1), (x2, y2) = parse_bbox(prediction, width, height)
# img = cv2.putText(img, prediction['tagName']+prob_str,
# (x1, y1-5), font, font_scale, (255, 255, 255), thickness)
text = prediction["tagName"] + prob_str
img = draw_label(img, text, (x1, max(y1, 15)))
return img
def draw_objs(self, img, is_id=True, is_rect=True):
for obj in self.tracker.get_objs():
font = cv2.FONT_HERSHEY_DUPLEX
font_scale = 0.7
thickness = 1
x1, y1, x2, y2, oid = obj
x1 = int(x1)
y1 = int(y1)
x2 = int(x2)
y2 = int(y2)
oid = int(oid)
x = x1
y = y1 - 5
if is_id:
img = draw_label(img, str(oid), (x, y))
if is_rect:
img = cv2.rectangle(img, (x1, y1), (x2, y2), (255, 255, 255), thickness)
return img