[模型分享] AI自學 4-Object_and_Pose_detection

def labels_string(boxes, labels):
    tmp = ""
    for box in boxes:
        tmp += "{},".format(labels[box[0]])
    if len(tmp) == 0:
        return "沒有物品正拿在手上"
    return tmp

def process_results(predictions):
    results = []
    for prediction in predictions:
        results.append((int(prediction[5]), prediction[4], (int(prediction[0]), int(prediction[1]), int(prediction[2]), int(prediction[3]))))
    return results

def calculate_dist(a, b):
    x=int(b[0])-int(a[0])
    y=int(b[1])-int(a[1])
    return np.sqrt(x*x+y*y)

w_image = widgets.Image(format='jpeg', width=640, height=480)
left_arm = widgets.Text(value='',placeholder='是否有手機?',description='左手:',disabled=False)
right_arm = widgets.Text(value='',placeholder='是否有手機?',description='右手:',disabled=False)
left_hand = widgets.Text(value='',placeholder='吃藥?',description='左手：',disabled=False)
right_hand = widgets.Text(value='',placeholder='吃藥?',description='右手：',disabled=False)
mouth = widgets.Text(value='',placeholder='吃藥?',description='嘴巴：',disabled=False)
medicine = widgets.Text(value='',placeholder='',description='有吃藥嗎：',disabled=False)
timeC = widgets.Text(value='',placeholder='',description='時間：',disabled=False)
alarm = widgets.Text(value='',placeholder='',description='鬧鐘：',disabled=False)
dlist = widgets.Dropdown(
    options = [('bottle') , ('waterbottle'), ('heart_medicine'), ('vitamin_c'), ('painkiller')], 
    value = 'bottle',
    description='Number:',
    disabled=False,
)
obj_type = 'bottle'
def headler(change):
    global obj_type
    print("change to:{}".format(change.new))
    obj_type = change.new
    print(obj_type)
    
dlist.observe(headler, names='value')
text_Contain = widgets.VBox([left_hand, right_hand, mouth, medicine, timeC, alarm, dlist])
Contain = widgets.HBox([w_image, text_Contain])




    # Main processing function to run object detection.
def run_object_detection(source=0, flip=False, skip_first_frames=0, alarmH=20, alarmM=0):
    global dlist
    player = None
    eat_medicine = 0
    try:
        # Create a video player to play with target fps.
        player = utils.VideoPlayer(
            source=source, flip=flip, fps=30, skip_first_frames=skip_first_frames
        )
        # Start capturing.
        player.start()

        processing_times = collections.deque()
        saved_pos = {'bottle' : [], 'waterbottle' : [], 'heart_medicine' : [], 'vitamin_c':[], 'painkiller':[]}
        #saved_pos =n boxes9
        
        with ui_events() as poll:
            while True:
                poll(10)
                # Grab the frame.
                frame = player.next()
                if frame is None:
                    print("Source ended")
                    break
                    
#                 boxes = DetectObj.get_boxes(frame)
                boxes = detect.detect_image(model, frame)
                boxes = process_results(boxes)
                poses, scores = PoseObj.get_results(frame)
        
                #print(boxes[0][0])
                frame = DetectObj.draw_boxes(frame, boxes)
                frame = PoseObj.draw_poses(frame, poses, 0.1) #ask 0.1
                
                
                if len(boxes) > 0:
                    for id, conf, pos in boxes:
                        if id == 0 : saved_pos['painkiller'] = [(id, conf, pos)]
                        if id == 1 : saved_pos['vitamin_c'] = [(id, conf, pos)]
                        if id == 2 : saved_pos['heart_medicine'] = [(id, conf, pos)]
                        if id == 3 : saved_pos['bottle'] =[(id, conf, pos)]
                        if id == 4 : saved_pos['waterbottle'] = [(id, conf, pos)]
                frame = DetectObj.draw_boxes(frame=frame, boxes=saved_pos[obj_type])
                   # print(dropdown.value)
                    # Draw boxes on a frame.
                    #frame = DetectObj.draw_boxes(frame=frame, boxes=boxes)
                    #frame = PoseObj.draw_poses(frame, poses, 0.1)
    
                for pose in poses:
                    left_arm.value = labels_string(_is_boxes_pose(boxes, pose[10], 200), DetectObj.get_my_labels())
                    right_arm.value = labels_string(_is_boxes_pose(boxes, pose[9], 200), DetectObj.get_my_labels())
                    break

                w_image.value = bgr8_to_jpeg(frame)
                for pose in poses:
                    left_hand.value = labels_string(_is_boxes_pose(boxes, pose[10], 250, 0.25), DetectObj.get_my_labels())
                    right_hand.value = labels_string(_is_boxes_pose(boxes, pose[9], 250, 0.25), DetectObj.get_my_labels())
                    mouth.value = labels_string(_is_boxes_pose(boxes, pose[0], 250, 0.25), DetectObj.get_my_labels())
                    if left_hand.value != "沒有" and calculate_dist(pose[10], pose[0]) < 250:
                        medicine.value = "你有吃藥耶你好棒"
                        eat_medicine = 1
                    if right_hand.value != "沒有" and calculate_dist(pose[10], pose[0]) < 250:
                        medicine.value = "你有吃藥耶你好棒"
                        eat_medicine = 1
                    if mouth.value != "沒有":
                        medicine.value = "你有吃藥耶你好棒"
                        eat_medicine = 1
                
                tonow = datetime.datetime.now()
                timeC.value = tonow.strftime('%Y/%m/%d %H:%M:%S')
                if tonow.hour>=alarmH and tonow.minute>=alarmM and eat_medicine == 0:
                    alarm.value = "吃藥啦 阿北"
                    medicine.value = "沒有"
                else:
                    alarm.value = ""
                
            
            w_image.value = bgr8_to_jpeg(frame)
            
    # ctrl-c
    except KeyboardInterrupt:
        print("Interrupted")
    # any different error
    except RuntimeError as e:
        print(e)
    finally:
        if player is not None:
            # Stop capturing.
            player.stop()