db44060a8de04f55557badee55cd617392d65c5b..ae7c39f6eb9989784f2d56c77cae944e967d6ef8
2022-03-25 zhangshiming
deal terme
ae7c39 对比 | 目录
2022-03-24 wangzhibo
识别宽的情况 人工拆分
9fda3f 对比 | 目录
5个文件已修改
6个文件已删除
3个文件已添加
78 ■■■■■ 已修改文件
DevOps.txt 补丁 | 查看 | 原始文档 | blame | 历史
__pycache__/delete_task.cpython-36.pyc 补丁 | 查看 | 原始文档 | blame | 历史
__pycache__/extract_voltage_task.cpython-36.pyc 补丁 | 查看 | 原始文档 | blame | 历史
debug/2_split_digit_from_video.py 1 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
debug/7122.mp4 补丁 | 查看 | 原始文档 | blame | 历史
debug/7222.mp4 补丁 | 查看 | 原始文档 | blame | 历史
debug/7322.mp4 补丁 | 查看 | 原始文档 | blame | 历史
debug/7422.mp4 补丁 | 查看 | 原始文档 | blame | 历史
debug/__pycache__/_image_clip_setting.cpython-36.pyc 补丁 | 查看 | 原始文档 | blame | 历史
debug/_image_clip_setting.py 6 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
debug/fail_.jpg 补丁 | 查看 | 原始文档 | blame | 历史
extract_voltage_task.py 34 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
main.py 24 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
safe.sh 13 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
DevOps.txt
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__pycache__/delete_task.cpython-36.pyc
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__pycache__/extract_voltage_task.cpython-36.pyc
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debug/2_split_digit_from_video.py
@@ -18,6 +18,7 @@
    contours, hierarchy = cv2.findContours(
        counter, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours_count = 0
    return_numbers = []
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        if hierarchy[0][contours_count][3] == 0 and h > image_h * 0.3:
debug/7122.mp4
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debug/7222.mp4
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debug/7322.mp4
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debug/7422.mp4
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debug/__pycache__/_image_clip_setting.cpython-36.pyc
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debug/_image_clip_setting.py
@@ -4,7 +4,7 @@
#image_clip = [176,234,278,422]     # for  video.mp4
#image_clip = [226,266,200,300]     # for  new.mp4
#image_clip = [220,275,210,300]     # test image
#image_clip = [220,275,210,300]  # for  7122.mp4
image_clip = [255,308,290,412]  # for  7222.mp4
image_clip = [220,275,210,300]  # for  7122.mp4
#image_clip = [255,308,290,412]  # for  7222.mp4
#image_clip = [229,274,270,380]  # for  7322.mp4
#image_clip = [180,240,154,287]   # for  7322.mp4
#image_clip = [180,240,154,287]   # for  7422.mp4
debug/fail_.jpg
extract_voltage_task.py
@@ -19,7 +19,7 @@
    digits.append([cv2.imread(path + "/0-0.jpg", cv2.IMREAD_GRAYSCALE), 0])
    digits.append([cv2.imread(path + "/0-1.jpg", cv2.IMREAD_GRAYSCALE), 0])
    digits.append([cv2.imread(path + "/0-2.jpg", cv2.IMREAD_GRAYSCALE), 0])
    digits.append([cv2.imread(path + "/0-3.jpg", cv2.IMREAD_GRAYSCALE), 0])
    digits.append([cv2.imread(path + "/0-3.jpg", cv2.IMREAD_GRAYSCALE), 0])
    digits.append([cv2.imread(path + "/1-0.jpg", cv2.IMREAD_GRAYSCALE), 1])
    digits.append([cv2.imread(path + "/1-1.jpg", cv2.IMREAD_GRAYSCALE), 1])
    digits.append([cv2.imread(path + "/2-0.jpg", cv2.IMREAD_GRAYSCALE), 2])
@@ -46,33 +46,38 @@
digits = []
def get_most_simmilar_digit(target_img):
def get_most_simmilar_digit(target_img,app):
    source = []
    #img_gray = cv2.cvtColor(target_img, cv2.COLOR_BGR2GRAY)
    #ret, binary = cv2.threshold(img_gray,0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    # 循环对比模板的图片
    app.logger.info("start identify")
    if len(digits) < 5:
        task_init_load_digits()
    for digitROI in digits:
        res = cv2.matchTemplate(target_img, digitROI[0], cv2.TM_CCOEFF_NORMED)
        max_val = cv2.minMaxLoc(res)[1]
        source.append(max_val)
    # print(max(source))
    #print(max(source))
    if max(source) > 0.3:
        app.logger.info(digits[source.index(max(source))][1])
        return digits[source.index(max(source))][1]
    else:
        return "@"
def extrct_digits_from_frame(frame, col_start, col_end, rows_start, rows_end):
def extrct_digits_from_frame(frame, col_start, col_end, rows_start, rows_end,app):
    image = frame[col_start:col_end, rows_start:rows_end]
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    thresh = cv2.threshold(gray, 0, 255,
                           cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (6, 6))
    counter = cv2.morphologyEx(thresh.copy(), cv2.MORPH_OPEN, kernel)
    contours, hierarchy = cv2.findContours(
        counter, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours, hierarchy = cv2.findContours(counter, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    return_numbers = []
    contours_count = 0
    image_h = image.shape[0]
@@ -80,31 +85,32 @@
    digit = -1
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        if hierarchy[0][contours_count][3] == 0 and h > image_h * 0.3:
            if w > image_w/4:
        if hierarchy[0][contours_count][3] ==0 and h > image_h * 0.3:
            if w>image_w/4:
                half_width = int(w/2)
                one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(
                    gray[y:y+h, x:x+half_width], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1])
                gray[y:y+h, x:x+half_width], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1],app)
                if one_number != '@':
                    return_numbers.append([x, one_number])
                else:
                    return digit, False
                one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(
                    gray[y:y+h, x+half_width:x+w], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1])
                gray[y:y+h, x+half_width:x+w], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1],app)
                if one_number != '@':
                    return_numbers.append([x+half_width, one_number])
                else:
                    return digit, False
            else:
                one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(
                    gray[y:y+h, x:x+w], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1])
                gray[y:y+h, x:x+w], (20, 30)), 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1],app)
                if one_number != '@':
                    return_numbers.append([x, one_number])
                else:
                    return digit, False
        contours_count += 1
    if len(return_numbers) == 0:
        return digit, False
        contours_count +=1
    if len(return_numbers)==0:
            return digit,False
    print(return_numbers)
    return_numbers = np.array(sorted(return_numbers))
    return_numbers = return_numbers[:, -1]
    if len(return_numbers) < 3:
main.py
@@ -115,12 +115,7 @@
         "JOBS": [{"id": "my_job", # 任务ID
                    "func": "__main__:extract_voltage_send",#任务位置
                    "trigger": "interval", #触发器
                    "seconds": 60 # 时间间隔
                    },
                   {"id": "my_job2", # 任务ID
                    "func": "delete_task:delete_old_images",#任务位置
                    "trigger": "interval", #触发器
                    "seconds": 60 # 时间间隔
                    "minutes": 1 # 时间间隔
                    }
                ]}
        )
@@ -129,25 +124,30 @@
def extract_voltage_send():
    print('extract_voltage_send job started!')
    time_now = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
    time_public=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    app.logger.info(time_now+' extract_voltage_send job started!')
    #camera = cv2.VideoCapture(0) #use 0 for web camera  deplyoment
    cap = cv2.VideoCapture('./debug/7422.mp4') # for testing
    cap = cv2.VideoCapture(0) # for testing
    #    以下设置显示屏的宽高
    cap.set(cv2.CAP_PROP_FRAME_WIDTH,    640)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT,    480)
    fails_count = 0 
    while True:
        ret, frame = cap.read()
        return_digital,job_status = extrct_digits_from_frame(frame,app.config['IMAGE_CLIP_COLS_START'],app.config['IMAGE_CLIP_COLS_END'],app.config['IMAGE_CLIP_ROWS_START'],app.config['IMAGE_CLIP_ROWS_END'])
        return_digital,job_status = extrct_digits_from_frame(frame,app.config['IMAGE_CLIP_COLS_START'],app.config['IMAGE_CLIP_COLS_END'],app.config['IMAGE_CLIP_ROWS_START'],app.config['IMAGE_CLIP_ROWS_END'],app)
        if job_status or fails_count > 10:
            #mqtt.publish(app.config['REMOTE_MQTT_PUBLISH_TOPIC'], "{'voltage':"+str(return_digital)+"}")
            mqtt.publish(app.config['REMOTE_MQTT_PUBLISH_TOPIC'], "{\"sn\":" + "\"" + app.config['MQTT_CLIENT_ID'] +"\"" + " , \"time\":"+ "\"" + time_now  +"\""+" , \"value\":"+ str(return_digital) +" }")
            cv2.imwrite("./imageframe/image_frame_"+time_now+".jpg", cv2.putText(frame, str(return_digital), (app.config['IMAGE_CLIP_ROWS_START'], app.config['IMAGE_CLIP_COLS_START']), cv2.FONT_HERSHEY_COMPLEX, 1.5, (0, 255, 255), 2))
            mqtt.publish(app.config['REMOTE_MQTT_PUBLISH_TOPIC'], "{\"sn\":" + "\"" + app.config['MQTT_CLIENT_ID'] +"\"" + " , \"time\":"+ "\"" + time_public  +"\""+" , \"value\":"+ str(return_digital) +" }")
            app.logger.info(" send the digital "+str(return_digital))
            cv2.imwrite("./image_frame/success_"+time_now+".jpg", cv2.putText(frame, str(return_digital), (app.config['IMAGE_CLIP_ROWS_START'], app.config['IMAGE_CLIP_COLS_START']), cv2.FONT_HERSHEY_COMPLEX, 1.5, (0, 255, 255), 2))
            app.logger.info("image is identified successful")
            cap.release()
            break
        else:
            fails_count +=1
            cv2.imwrite("./fails/image_frame_"+time_now+".jpg", frame)
            app.logger.info("image is identified fail=======")
            cv2.imwrite("./fails/fail_"+time_now+".jpg", frame)
    #if need_send _image :
    #    send_image
@@ -180,7 +180,7 @@
    AddJobConfig()     # 配置任务,不然无法启动任务
    scheduler.init_app(app)
    scheduler.start()
    app.logger.info("scheduler is running......")
    #app.run()
    socketio.run(app, host='0.0.0.0', port=8058, debug=True)
    #mqtt.subscribe(app.config['REMOTE_MQTT_SUBSCRIBE_TOPIC'])  // need to wait for mqtt client finished connection
safe.sh
New file
@@ -0,0 +1,13 @@
#!/bin/sh
if test $( pgrep -f main | wc -l ) -eq 0
then
/home/pi/huaneng/main.sh
echo "no"
else
echo "yes"
fi