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82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
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import cv2
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from pipeline_atm_getResult import atm_det
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def analysis_pph(imagepath,model_pp_hand,score_person):
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pph_re_list = []
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score_pp_hand = atm_det.get_pph_result(imagepath,model_pp_hand)
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for pp_dic in score_pp_hand:
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person_bbox = list(score_person[0].values())[0]
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pp_bbox = list(pp_dic.values())[0]
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# print(person_bbox,pp_bbox)
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# 判断检测到的手部动作是否是工作人员,防止误识别客户的手部动作
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# if int(pp_bbox[0]) and int(pp_bbox[2]) in range(int(person_bbox[0]),int(person_bbox[2])) and int(pp_bbox[1]) and int(pp_bbox[3]) in range(int(person_bbox[1]),int(person_bbox[3])):
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if int(pp_bbox[0]) and int(pp_bbox[2]) in range(int(person_bbox[0]),int(person_bbox[2])):
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# text_pph = ('Wrong action with',list(pp_dic.keys())[0])
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pph_re_dict = {list(pp_dic.keys())[0]:pp_bbox}
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pph_re_list.append(pph_re_dict)
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# 加入图片输出
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# print('Wrong action with',list(pp_dic.keys())[0])
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else:
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continue
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return pph_re_list
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def analysis_button(imagepath,score_button,score_person):
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img = cv2.imread(imagepath)
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w,h,t = img.shape
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x_mid = w/2
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re_list = []
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for score_blue in score_button:
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# 选择右侧按键
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# if ((score_blue[2] + score_blue[0])/2 + score_blue[0]) >= x_mid:
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person_bbox = list(score_person[0].values())[0]
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# 判断检测到的手部动作是否是工作人员,防止误识别客户的手部动作
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if int(score_blue[0]) and int(score_blue[2]) in range(int(person_bbox[0]),int(person_bbox[2])):
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# if int(score_blue[0]) and int(score_blue[2]) in range(int(person_bbox[0]),int(person_bbox[2])) or int(score_blue[1]) and int(score_blue[3]) in range(int(person_bbox[1]),int(person_bbox[3]))
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# text_pph = ('Wrong action with',list(score_blue.keys())[0])
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# pph_re_dict = {text_pph:pp_bbox}
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re_list.append(score_blue)
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pass
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# 加入图片输出
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# print('Wrong action with',list(pp_dic.keys())[0])
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else:
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# re_list.append('button action is right.')
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pass
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# else:
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# # button_dict ={'button_dict_right':{imagepath:score_blue}}
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# # re_list.append('button action is right.')
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# pass
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# print(re_list)
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# if len(re_list) == 0:
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# re_list.append('button action is right.')
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# print(re_list)
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return re_list |