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質問の訂正

2020/09/25 04:59

投稿

noooooooob

スコア16

test CHANGED Viewed

File without changes

test CHANGED Viewed

@@ -50,469 +50,7 @@
-import sys
-from PyQt5.QtWidgets import *
-from PyQt5.QtGui import *
-from PyQt5.QtCore import *
-import subprocess
-import time
-import numpy as np
-import cv2
-import math
-import RPi.GPIO as GPIO
-import image_processing
-import HSV
-import motor
-import Gyro
-class Tab1Widget(QWidget):
-    def __init__(self):
-        super().__init__()
-        self.title = "自律走行車"
-        self.left = 50
-        self.top = 50
-        self.width = 1300
-        self.height = 1200
-        self.initUI()
-        self.counter = 0
-    def initUI(self):
-        super(Tab1Widget, self).__init__()
-        self.cap = cv2.VideoCapture(0)
-        self.cap.set(cv2.CAP_PROP_FRAME_WIDTH,320)
-        self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT,240)
-        self.cap.set(cv2.CAP_PROP_FPS,10)
-        self.camera_run = 0
-        self.auto_run = 0
-        self.countM = 0
-        self.M = 1
-        self.Duty_R = self.Duty_L  = 0
-        self.Pitch=0
-        self.Roll=0
-        self.H1 = 30
-        self.H2 = 90
-        self.countHSV2 = 0
-        self.view1 = QGraphicsView()
-        self.scene1 = QGraphicsScene()
-        self.view2 = QGraphicsView()
-        self.scene2 = QGraphicsScene()
-        （GUIの設定なので中略）
-        簡単に説明
-        ・GUI上のボタン「カメラスタート」を押すとカメラの出力画像をGUI上に表示
-        ・また、カメラの傾きを考慮した画像処理を行っていおり、実際に画像処理される範囲をGUI上に表示（これが今回のしたいことです）
-        ・GUI上のボタン「自律移動スタート」を押すと画像処理の情報を元に自律移動する
-    def camera_start(self):
-        self.camera_run = 1
-        #サーボモータ(正面カメラ)のsetup
-        Servo_pin=18
-        GPIO.setmode(GPIO.BCM)
-        GPIO.setup(Servo_pin, GPIO.OUT)
-        self.Servo = GPIO.PWM(Servo_pin, 50)
-        self.Servo.start(0)
-        self.camera_set()
-        repeatTime = 300
-        timer = QTimer(self.view1
-        timer.timeout.connect(self.camera_set)
-        timer.start(repeatTime)
-    def camera_stop(self):
-        self.camera_run = 0##カメラOFF
-    def camera_set(self):
-        #Gyro.pyからデータ取得
-        self.Pitch, self.Roll = Gyro.GyroSensor(self.Pitch, self.Roll)
-        #テキストにピッチ角、ロー角を出力
-        pitch = str(round(self.Pitch))
-        self.textbox7.setText(pitch + "°")
-        roll = str(round(self.Roll))
-        self.textbox8.setText(roll + "°")
-        ret, cv_img = self.cap.read()
-        if ret == False:
-            return
-        #カメラの角度制御
-        def servo_angle(angle):
-            duty = 2.5 + (12.0 - 2.5) * (angle + 90) / 180
-            self.Servo.ChangeDutyCycle(duty)
-        #ピッチ角分サーボを回転
-        servo_angle(round(self.Pitch))
-        #サーボモータをストップ
-        self.Servo.stop()
-        #ロー角分画像回転
-        height = cv_img.shape[0]
-        width = cv_img.shape[1]
-        center = (int(width/2),int(height/2))
-        angle = round(self.Roll*(-1))
-        scale = 1.0
-        trans = cv2.getRotationMatrix2D(center,angle,scale)
-        self.cv_img = cv2.warpAffine(cv_img,trans,(width,height))
-        #グレースケール変換
-        cv_img_RGB = cv2.cvtColor(self.cv_img,cv2.COLOR_BGR2RGB)
-        #リサイズ
-        cv_img_RGB = cv2.resize(cv_img_RGB,(320,240))
-        #画像処理範囲を赤枠で囲む(分かりやすいように)
-        cv_img_RGB = cv2.rectangle(cv_img_RGB, (40-round(460.7016*math.cos(math.radians(90-self.Roll))), 90), (280-round(460.7016*math.cos(math.radians(90-self.Roll))), 240), (255, 0, 0), 2, 3)
-        height, width, dim = cv_img_RGB.shape
-        bytesPerLine = dim * width
-        self.image1 = QImage(cv_img_RGB.data, width, height, bytesPerLine, QImage.Format_RGB888)
-        self.item1 = QGraphicsPixmapItem(QPixmap.fromImage(self.imag1e))
-        self.scene1.addItem(self.item1)
-        self.view1.setScene(self.scene1)
-        self.img_src = self.cv_img
-        print("あいうえお")
-        #画像処理範囲を切り抜いた画像をGUI上に出力
-        #画像処理した画像をimage_processing.pyから持ってくる
-        pixel, img_src0, elapsed_time, self.countM, img_dst3  = image_processing.img_process(self.auto_run,self.img_src,self.countM,self.H1,self.H2, self.Roll)
-        #マスク処理を施した画像を表示
-        height2, width2, dim2 = img_dst3.shape
-        bytesPerLine2 = dim2 * width2
-        self.image2 = QImage(img_dst3.data, width2, height2, bytesPerLine2, QImage.Format_RGB888)
-        self.item2 = QGraphicsPixmapItem(QPixmap.fromImage(self.image2))
-        self.scene2.addItem(self.item2)
-        self.view2.setScene(self.scene2)
-        #
-        pixcel = str(round(pixcel,3))
-        self.textbox4.setText(picxel)
-        elapsed_time = str(round(elapsed_time,3))
-        self.textbox5.setText(elapsed_time)
-        #出力データをファイルに書き込み
-        MPU= open('/home/pi/Desktop/data','a')
-        MPU.write(   "Pitch:"+pitch+""+"Roll:"+roll + "\n")
-        MPU.close
-    def auto_move(self):
-        self.auto_run = 1
-        以下　自律移動を行うためのコード(省略)
-if __name__ == "__main__":
-    app = QApplication(sys.argv)
-    ex = Tab1Widget()
-    sys.exit(app.exec_())
-```
-```python
-ファイル名:image_processing.py
-import numpy as np
-import math
-import cv2
-import time
-import P_data
-import HSV
-import motor
-import RPi.GPIO as GPIO
-def img_process(auto_run,img_src,countM,H1,H2,Roll):
-    t1 = time.time()
-    if auto_run == 0:
-            return
-    M = 1
-    #画像サイズ変更(処理速度に応じて変更すべし）
-    img_src=cv2.resize(img_src,(320,240))
-    img_src=img_src[90:240, 40-round(460.7016*math.cos(math.radians(90-Roll))):280-round(460.7016*math.cos(math.radians(90-Roll)))]
-    hsv = cv2.cvtColor(img_src, cv2.COLOR_BGR2HSV)
-    img_src0 = cv2.cvtColor(img_src, cv2.COLOR_BGR2RGB)
-    lower_green = np.array([H1, 50, 30])
-    upper_green = np.array([H2, 255,255])
-    img_mask = cv2.inRange(hsv, lower_green, upper_green)
-    neiborhood8 = np.array([[1, 1, 1],[1, 1, 1],[1, 1, 1]],np.uint8)
-    img_erosion = cv2.erode(img_mask,neiborhood8,iterations=2)
-    img_erosion = cv2.erode(img_erosion,neiborhood8,iterations=2)
-    img_dilation = cv2.dilate(img_erosion,neiborhood8,iterations=2)
-    img_dilation = cv2.dilate(img_dilation,neiborhood8,iterations=2)
-    img_dst = cv2.bitwise_and(img_src, img_src, mask=img_dilation)
-    img_dst2 = cv2.bitwise_and(img_src, img_src, mask=img_mask)
-    img_dst3 = cv2.bitwise_and(img_src, img_src, mask=img_dilation)
-    start = time.time()
-    row_mean_L , row_mean_R ,pixcel = P_data.Get_MotorParameter(img_mask, 1, F3)
-    F3 = int(-pixcel)
-    count_hsv += 1
-    if count_hsv == 20 or count_hsv == 25 or count_hsv == 30  :
-        img_dst, H1, H2 ,S1 , S2 , countHSV2 = HSV.HSV_value (img_dst, H1, H2,countHSV2)
-    countM += 1
-    t2 = time.time()
-    elapsed_time = t2 - t1
-    return pixcel, img_src0, elapsed_time, countM, img_dst3
 ```
@@ -528,7 +66,7 @@
 しかし、その下にある
-> pixel, img_src0, elapsed_time, self.countM, img_dst3  = image_processing.img_process(self.auto_run,self.img_src,self.countM,self.H1,self.H2, self.Roll)
+>