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