Exemple #1
0
def receiver(client, addr):
    global counter
    counter += 1  # 스레드 별로 imshow에서 사용할 타이틀을 다르게 하기 위해서
    frame_name = f'frame{counter}'

    reader = client.makefile('rb')
    writer = client.makefile('wb')
    while True:
        data, data_len = net2.receive(reader)
        if not data:
            break
        # print('received ', data_len)  # 이미지 처리
        # AI 알고리즘 처리 - 불량 여부 판단... 여기에 넣으면됭
        show_image(data, frame_name)
        result = json.dumps({'result': 'ok'})
        net2.send(writer, result.encode())

    print('exit receiver')
def receiver(client, addr):
    reader = client.makefile('rb')
    # writer = client.makefile('wb')

    while True:
        data, data_len = net2.receive(reader)
        print('-------수신 ')
        if not data_len:
            return
        # data : jpeg 이미지
        # image : bgr 이미지
        ret, image = show_image(data)
        # AI 알고리즘 처리
        cv2.imshow('image', image)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cv2.destroyAllWindows()
    print('exit receiver')
Exemple #3
0
def vido_streaming():
    with socket.socket() as s:
        s.connect((HOST,PORT))
        writer = s.makefile('wb')
        reader = s.makefile('rb')
        stream=io.BytesIO()

        for _ in camera.capture_continuous(stream,'jpeg',use_video_port=True):
            image=stream.getvalue()

            net2.send(writer,image)
            result=net2.receive(reader)[0]
            stream.seek(0)
            stream.truncate()

            if not button.is_pressed:
                writer.write(struct.pack('<L',0))
                writer.flush()
                break
def receiver(client, addr):
    global count
    # count += 1
    filename = count
    reader = client.makefile('rb')
    # writer = client.makefile('wb')

    data, data_len = net2.receive(reader)
    # print('-------수신 ')
    if not data_len:
        return
    # data : jpeg 이미지
    # image : bgr 이미지
    image, key = show_image(data)
    # cv2.imwrite("test" + str(count) + ".jpg"  , image)
    # print(image)
    # AI 알고리즘 처리
    cv2.imshow(str(filename), image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
def receiver(client, addr , model):
    print('\n\n\n#####################################################\n')
    asyncio.set_event_loop(asyncio.new_event_loop())

    # �ð� �������� ��������
    current_time = datetime.now() + timedelta(hours=9)
    current_time = current_time.strftime("%m%d%H%M%S.%f")[:-3]
    current_time = current_time.replace("." , "")


    print("#####################")
    print(current_time)
    print("#####################")
    ###############################
    # 1. �̹��� ���� �� ����      #
    ###############################
    

    print("="*40)
    print('Receiver start')
    print("="*40)

    reader = client.makefile('rb')
    data, data_len = net2.receive(reader)
    if not data_len:
        return
    image, key = show_image(data)
    
    # ī�޶� �׽�Ʈ �̹���
    file_name = "test"
    cv2.imwrite("./" + file_name + ".jpg" , image)

    
    ###############################
    # 2. AI - �з�                #
    ###############################


    
    
    ## YOLO ����
    NAME_CFG = "yolov4_CASHER_v6.cfg"
    NAME_WEIGHT = "yolov4_CASHER_v6_best.weights"
    os.system('./darknet detector test data/obj.data ' + NAME_CFG + " " + NAME_WEIGHT + " test.jpg"  + " -thresh 0.5 -out result.json")
    os.system('mv predictions.jpg ./predictions/' + "result_" + current_time + ".jpg")
    os.system('mv result.json ./predictions/' + "result_" + current_time + ".json")

    
    ## OBJECT DETECTION ���
    json_file_name = "result_" + current_time + ".json"
    with open('./predictions/' + json_file_name , 'r') as f:
      json_data = json.load(f)
    print(json_data)
    
    THRESHOLD = 0.7   
    ITEM_LST = []
    RESULT = 1
    
    for item_data in json_data[0]["objects"]:
      item_dict = {}
      item_dict["id"] = item_data["name"]
      item_dict["prob"] = item_data["confidence"]
      item_dict["outcome"] = 1 
      if item_dict["prob"] > THRESHOLD :
        item_dict["outcome"] = 1
      else:
        item_dict["outcome"] = 0
        RESULT = 0
      ITEM_LST.append(item_dict)
      


#     ###############################
#     # 3. Ŭ���� ���� �۽�       #
#     ###############################       
                 
    print("="*40)
    print('Send Server start')
    print("="*40)
    
    

    

    
    ## 1. REST_API >> S3 ���
    REST_API_DICT = {}
    REST_API_DICT["result"] = RESULT
    REST_API_DICT["time"] = current_time
    REST_API_DICT["item"] = ITEM_LST
    response_1 = send_REST_API(REST_API_DICT)
    print("REST-API SERVER")
    print(response_1)
    
    ## 3. BOTO3 >> S3 ���
    if RESULT == False:
      response_2 = send_S3( "./predictions/" + "result_" + current_time + ".jpg" , "result_" + current_time + ".jpg" )
      print("BOTO3 SERVER")
      print(response_2)
    
    
    ## 4. WEBSOCKET >> WEB ���
    WEB_DICT = {}
    WEB_LST = []
    
    for item in ITEM_LST:
      item_dict = {}
      
      item_dict["id"] = YOLO_CONVERT_INDICATOR[item["id"]]  
      item_dict["name"] = DF[DF["Item_id"]==int(item_dict["id"])]["Product_name"].values[0]
      item_dict["price"] = int(DF[DF["Item_id"]==int(item_dict["id"])]["Price"].values[0])
      item_dict["Qty"] = 1
      WEB_LST.append(item_dict)
      
    WEB_DICT["item"] = WEB_LST
    asyncio.get_event_loop().run_until_complete(connect(WEB_DICT))
Exemple #6
0
def receiver(client, addr , model):
    #print('\n\n\n#####################################################\n')

    asyncio.set_event_loop(asyncio.new_event_loop())
    ###############################
    # 1. 이미지 수신 및 저장      #
    ###############################
    print('\n\n\n')
    print("="*100)
    print('Receiver start')
    print("="*100)
    
    reader = client.makefile('rb')
    data, data_len = net2.receive(reader)
    if not data_len:
        return
    image, key = show_image(data)
    
    # 현재 시간 기준으로 파일명 저장
    current_time = time.time()
    current_ms = str(int(round(current_time * 1000)))[-3:]
    current_time = time.strftime(f'%m%d%H%M%S{current_ms}', time.localtime(current_time))

    file_name = "result_"  + current_time + '.jpg' # result_0601135334123.jpg (6월 1일 13시 53분 34.123초)
    print(f'\n#\n# File Name : {file_name}\n#\n')
    cv2.imwrite("./History/" + file_name, image)
    
    
    ###############################
    # 2. AI - 분류                #
    ###############################

    THRESHHOLD = 0.9
    
    
    # 이미지 Resize
    
    input_arr = resize(image, (200,200)) / 255
    input_arr = np.array([input_arr]) # Convert single image to a batch.
    input_arr = input_arr[:,:,:,::-1] # GBR to RGB
    

    
    
    # Model predict
    prob = MODEL.predict(input_arr)[0]
    pred = prob.argmax()
    prob = prob[pred]
    
    # 더미값
    primary_key = int(indicate_key[pred])
    
    result = 1 if prob > THRESHHOLD else 0
    
    print('\n#\n# 예측 결과\n#\n')
    print(f'Predict Index : {pred}    name : {indicate[pred]}')
    print(f'Probability : {prob}')
    print(f'Primary Key : {primary_key}\n')

          
    ###############################
    # 3. 클라우드 서버 송신       #
    ###############################       
            
    ## 1. SOCKET >> IOT 통신
    
    if FAIL_IOT:
      print('Start IoT socket...')
      sendData = str(result)
      connectionSock.send(sendData.encode('utf-8'))
      connectionSock.send(sendData.encode('utf-8'))

    
    # 클라우드 서버에 송신할 데이터 생성
    send_data = {'result' :  result , 'time' :  current_time , 'item' : [] }
        
    result_item =  {
          "outcome": result,
          "id": str(primary_key), # Type : string
          "prob": int(prob*100)
        }

    ## REST-API 보내는 데이터
    send_data['item'].append(result_item)
    
    
    
    ITEM_DICT = {'item' : []}
    
    item_info = DF[DF['Item_id'] == primary_key] # SELECT * FROM table WHERE Item_id = primary_key
    
    temp_dict = {
        'id' : primary_key,
        'name' : item_info['Product_name'].values[0],
        'price' : int(item_info['Price'].values[0]),
        'Qty' : 1
    }
    
    ITEM_DICT['item'].append(temp_dict)
    
    if result :
        asyncio.get_event_loop().run_until_complete(connect(ITEM_DICT))


    # 서버 송신 (분류 성공 >> REST-API , 분류 실패 >> REST-API / S3)
    response = send_REST_API(send_data)
    if not result : send_S3(file_name) # 분류 실패 시 S3에 이미지파일도 전송

    print(f'서버 송신 결과 : {response}')