change countours method

wangzhibo

2022-03-14 7f3430f95dda8bc60e00b07e22c0de6cd9fba760

change countours method

 debug/0_get_frame.py

@@ -3,6 +3,7 @@

import datetime
import cv2
from _image_clip_setting import image_clip

time_now = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
#cap = cv2.VideoCapture(0)
@@ -12,6 +13,7 @@
print('手动设置 唯一的参数: 数字仪表盘的位置: 要稍微留些余量。')
print('格式为图像区域 [Y轴 min:max, X轴 min:max],如[176:234,280:426]')
print('另外图形 左上角为0,0 向右 为X轴正向，向下为Y轴正向')
cv2.imwrite(time_now+"_clip.jpg",frame[176:234,280:426])
cv2.imwrite(time_now+"_clip.jpg",
            frame[image_clip[0]:image_clip[1], image_clip[2]:image_clip[3]])
cap.release()
cv2.destroyAllWindows()

 debug/0_get_video.py

@@ -7,6 +7,7 @@
import cv2
import getopt
import sys
from _image_clip_setting import image_clip


def start_check_opts(argv):

 debug/1_check_frame_boundary.py

@@ -4,26 +4,26 @@
from cv2 import waitKey
import getopt
import sys

from _image_clip_setting import image_clip


def check_frame(frame):
    #image = frame[176:234,280:426]     
    image = frame[180:230,250:370]  #frame[176:234,280:426]

    #cv2.imshow('src',image)
    image = frame[image_clip[0]:image_clip[1], image_clip[2]:image_clip[3]]
    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)
    image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(counter,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE)
    contours, hierarchy = cv2.findContours(counter,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    contours_count = 0
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        if image_h*0.98 > h > image_h * 0.3:
            #print((x, y, w, h))
        if hierarchy[0][contours_count][3] ==0 :
        #if image_h*0.98 > h > image_h * 0.6:
            print((x, y, w, h))
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
        contours_count += 1
    cv2.imshow('frame',image)
    waitKey(0)


 debug/1_check_video_boundary.py

@@ -4,28 +4,31 @@
import cv2
from cv2 import waitKey
import uuid
from _image_clip_setting import image_clip


def check_frame(frame):
    image = frame[180:230,250:370]  #frame[176:234,280:426]
    image = frame[image_clip[0]:image_clip[1], image_clip[2]:image_clip[3]]
    #cv2.imshow('src',image)
    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)
    image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(counter,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE)
    contours, hierarchy = cv2.findContours(counter,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    contours_count = 0
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        if image_h*0.98 > h > image_h * 0.3:
            #print((x, y, w, h))
        if hierarchy[0][contours_count][3] ==0 :
        #if image_h*0.98 > h > image_h * 0.6:
            print((x, y, w, h))
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
        contours_count += 1
    cv2.imshow('frame',image)
    if cv2.waitKey(100) & 0xFF == ord('q'): #按q退出
        cv2.waitKey(0)
        
cap = cv2.VideoCapture("video2.mp4")  # for testing
cap = cv2.VideoCapture("video.mp4")  # for testing
while(cap.isOpened()):
    ret, frame = cap.read()
    if ret==True:

 debug/2022-03-12-20-15-24.jpg

Binary files differ

 debug/2022-03-12-20-15-24_clip.jpg

Binary files differ

 debug/2_check_frame_digits.py

@@ -5,6 +5,7 @@
import getopt
import sys
import numpy as np
from _image_clip_setting import image_clip


def task_init_load_digits():
@@ -62,23 +63,20 @@


def check_frame(frame):
    #image = frame[176:234, 280:426]
    image = frame[170:240,250:370]  #frame[176:234,280:426]
    cv2.rectangle(image, (250, 170), (370, 240), (0, 255, 0), 2)
    cv2.imshow('rect',image)
    waitKey(0)
    image = frame[image_clip[0]:image_clip[1], image_clip[2]:image_clip[3]]
    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)
    image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(
        counter, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
    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 image_h*0.98 > h > image_h * 0.3:
        if hierarchy[0][contours_count][3] ==0 :
        #if image_h*0.98 > h > image_h * 0.6:
            print((x, y, w, h))
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
            one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(
@@ -87,6 +85,7 @@
                return_numbers.append([x, one_number])
            else:
                return return_numbers, False
        contours_count += 1     
    return_numbers = np.array(sorted(return_numbers))
    return return_numbers[:, -1], True

@@ -111,5 +110,4 @@
    print(digit)
    cv2.putText(image, str(digit), (280, 170), cv2.FONT_HERSHEY_COMPLEX, 1.0, (100, 200, 200), 5)
    cv2.imshow('add_text',image)
    waitKey(0)

    waitKey(0)

 debug/2_check_video_digits.py

@@ -3,15 +3,9 @@
import time
import cv2
from cv2 import waitKey
import uuid

# -*- coding: utf-8 -*-
import datetime
import cv2
from cv2 import waitKey
import getopt
import sys
import numpy as np
import uuid
from _image_clip_setting import image_clip


def task_init_load_digits():
@@ -70,8 +64,7 @@


def get_digit(frame):
    image = frame[177:233,250:370]  #frame[176:234,280:426]
    # cv2.imshow('src',image)
    image = frame[image_clip[0]:image_clip[1], image_clip[2]:image_clip[3]]
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    thresh = cv2.threshold(gray, 0, 255,
                           cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
@@ -79,12 +72,13 @@
    counter = cv2.morphologyEx(thresh.copy(), cv2.MORPH_OPEN, kernel)
    image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(
        counter, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
        counter, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    contours_count = 0
    return_numbers = []
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        print((x, y, w, h))
        if image_h*0.98 > h > image_h * 0.3:
        if hierarchy[0][contours_count][3] ==0 :
        #if image_h*0.98 > h > image_h * 0.3:
            #print((x, y, w, h))
            #cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
            one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(
@@ -94,6 +88,7 @@
            else:
                return return_numbers, False
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
        contours_count += 1 
    cv2.imshow('frame', image)
    return_numbers = np.array(sorted(return_numbers))
    return return_numbers[:, -1], True
@@ -116,23 +111,23 @@
            # do got another image
            print('fails') 
            fail_count += 1
            cv2.rectangle(frame, (250, 177), (370, 233), (0, 255, 0), 2)
            cv2.rectangle(frame, (image_clip[2], image_clip[0]), (image_clip[3], image_clip[1]), (0, 255, 0), 2)
            cv2.imwrite('./fails/count_fail_'+str(uuid.uuid1())+'.jpg',frame)

    else:
        print('fails')
        fail_count +=1
        cv2.rectangle(frame, (250, 177), (370, 233), (0, 255, 0), 2)
        cv2.rectangle(frame, (image_clip[2], image_clip[0]), (image_clip[3], image_clip[1]), (0, 255, 0), 2)
        cv2.imwrite('./fails/status_fail_'+str(uuid.uuid1())+'.jpg',frame)
    print(round(digit,2))
    cv2.putText(frame, str(round(digit,2)), (280, 170),
    cv2.putText(frame, str(round(digit,2)), (image_clip[2], image_clip[0]-50),
                cv2.FONT_HERSHEY_COMPLEX, 1.0, (100, 200, 200), 5)
    cv2.imshow('add_text', frame)
    if cv2.waitKey(5) & 0xFF == ord('q'):  # 按q退出
        cv2.waitKey(0)


cap = cv2.VideoCapture("video2.mp4")  # for testing
cap = cv2.VideoCapture("video.mp4")  # for testing
total_frame = 0 
while(cap.isOpened()):
    ret, frame = cap.read()

 debug/__pycache__/_image_clip_setting.cpython-36.pyc

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 debug/_image_clip_setting.py

New file
@@ -0,0 +1,4 @@
# -*- coding: utf-8 -*-
__author__ = '上海色宁'

image_clip = [176,234,278,422]     # for  video.mp4

 debug/test.mp4

Binary files differ

 extract_voltage_task_new.py

@@ -69,13 +69,14 @@
                           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)
    image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(
        counter, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
    #image_h = image.shape[0]
    contours, hierarchy = cv2.findContours(counter, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    return_numbers = []
    contours_count = 0
    for c in contours:
        x, y, w, h = cv2.boundingRect(c)
        if image_h*0.98 > h > image_h * 0.3:
        #if image_h*0.98 > h > image_h * 0.3:
        if hierarchy[0][contours_count][3] ==0 :
            #print((x, y, w, h))
            #cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
            one_number = get_most_simmilar_digit(cv2.threshold(cv2.resize(