# 暑假大爆發

[TOC]

## 8/12
1. 安裝Jetpcak 4.2 (opencv 3.3.1, Cuda 10.0)
2. 有door.cfg 缺對應的 weights **使用door.yaml即可**

## 8/13
1. DVL 界面 work (下載官網Nortek Discover) [Link](https://www.nortekgroup.com/software?i)
4. ZED SDK and ZED ros wrapper
5. 用Arduino讀到MPU9250 data [Ref](https://hackmd.io/Wth1-ZdVROSO5xjWDoEjEA#Install-MPU9250-Arduino-LIbrary)
6. 讀PID
-----
- 子昊玩方向盤（駕訓班第一天）
- 昀洛畢業證書
- 水聽桶子換水
- **生智學會吹口哨**
-----

Arduino code

// https://github.com/hideakitai/MPU9250

#include "MPU9250.h"

MPU9250 mpu;

struct Imu
{
    float ax, ay, az;
    float gx, gy, gz;
    float mx, my, mz;
    float roll, yaw, pitch;
};


void setup()
{
    Serial.begin(9600);

    Wire.begin();

    delay(2000);
    mpu.setup();
}

void loop()
{
    static uint32_t prev_ms = millis();
    if ((millis() - prev_ms) > 90) // 0.1s
    {
        mpu.update();
        // mpu.print();
        
        // Direct use write() to sedn buffer data
        Imu data = {mpu.getAcc(0), mpu.getAcc(1), mpu.getAcc(2),
                    mpu.getGyro(0), mpu.getGyro(1), mpu.getGyro(2),
                    mpu.getMag(0), mpu.getMag(1), mpu.getMag(2),
                    mpu.getRoll(), mpu.getYaw(), mpu.getPitch()};
        Serial.write((byte*)&data, sizeof(data));
        Serial.write(10);

        // Could use print() & println() to sedn over String
        /*
        Serial.print(mpu.getAcc(0));
        Serial.print(" ");
        Serial.print(mpu.getAcc(1));
        Serial.println();
        */

        prev_ms = millis();
    }
}

用 Pyserial 在TX2讀出

#!/usr/bin/env python3

import serial
from struct import *
# import rospy
# from std_msgs.msg import String
# from std_msgs.msg import Float32
# from sensor_msgs.msg import Imu

port = '/dev/ttyACM0'

arduino = serial.Serial(port, 9600, timeout=1)
if not arduino.is_open:
    arduino.open()

a = 1
# for i in range(30):
#     data_raw = arduino.readline()
    
while(arduino.is_open):
    a += 1
    data_raw = arduino.readline()
    # data = tuple()
    try:
        data = unpack('ffffffffffffc', data_raw)
        print(a, data)
    except Exception as e:
        print('length: '+ str(len(data_raw)))
        print(e)
    '''
    readline() until asscii 10
    Serial.write(10)
    '''
    # print(a, data_raw)

## 8/14
1. 發現tx2開發板不支援PWM

## 8/25
1. 整理 github Controller repo 的 branch
2. 測試同時兩顆馬達的運轉狀況 -> 良好
3. **要確保不會短路**
4. 測試 mpu9250 的 PID code

## 8/26
### 育騰大爆發

import cv2
import numpy as np
from matplotlib.pyplot import imshow
from matplotlib import pyplot as plt
from scipy.stats import linregress
import matplotlib.pyplot as plt
%matplotlib inline


img = cv2.imread('floor.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
bw = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, \
                                cv2.THRESH_BINARY, 15, -2)


kernel_size = 5
blur_gray = cv2.GaussianBlur(gray,(kernel_size, kernel_size),0)
low_threshold = 20
high_threshold = 50
edges = cv2.Canny(blur_gray, low_threshold, high_threshold)


rho = 5               # distance resolution in pixels of the Hough grid
theta = np.pi / 180   # angular resolution in radians of the Hough grid
threshold = 100     # minimum number of votes (intersections in Hough grid cell)
min_line_length = 25  # minimum number of pixels making up a line
max_line_gap = 10     # maximum gap in pixels between connectable line segments
line_image = np.copy(img) * 0  # creating a blank to draw lines on
lines = []
# Run Hough on edge detected image
# Output "lines" is an array containing endpoints of detected line segments
lines = cv2.HoughLinesP(edges, rho, theta, threshold, np.array([]),
                    min_line_length, max_line_gap)
count=0
for line in lines:
    count+=1
    for x1,y1,x2,y2 in line:
        cv2.line(line_image,(x1,y1),(x2,y2),(255,0,0),5)
        # Draw the lines on the  image
    
lines_edges = cv2.addWeighted(img, 0.8, line_image, 1, 0)


# x1 x2 y1 y2 can form a line 
lines = lines.reshape(count,4)
slope = []
for i in range(count):
    x_coordinate = []
    y_coordinate = []
    for j in range(4): 
        if j%2:
            y_coordinate.append(lines[i][j])   #y coordinate for y1 y2
        else:
            x_coordinate.append(lines[i][j])   #x coordinate for x1 x2
   
    #do a linear regression to get slope of line
    result = linregress(x_coordinate, y_coordinate)
    # got the degree by slope
    result = np.degrees(np.arctan(result[0]))
    
    
    # turn two slope into the same theta
    if abs(result)>45:
        slope.append(abs(result))
    else:
        slope.append(90-abs(result))
        
#delete the nan
slope = [slope for slope in slope if str(slope) != 'nan']

#average all possible slope
if len(slope) >0:
    s = sum(slope)/len(slope)
    print(s)
plt.imshow(lines_edges)
plt.show


/

- yaw 最終版本：超過45度就不準了

import numpy as np
import cv2
import time
from matplotlib.pyplot import imshow
from matplotlib import pyplot as plt
from scipy.stats import linregress
import matplotlib.pyplot as plt
from numpy import *
import sys
%matplotlib inline


cap = cv2.VideoCapture(0)


while(True):
    #cv2.waitKey(delay_time)
    

    ret, frame = cap.read()
    
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    bw = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, \
                                cv2.THRESH_BINARY, 15, -2)
    kernel_size = 5
    blur_gray = cv2.GaussianBlur(gray,(kernel_size, kernel_size),0)
    low_threshold = 20
    high_threshold = 50
    edges = cv2.Canny(blur_gray, low_threshold, high_threshold)
    rho = 6               # distance resolution in pixels of the Hough grid
    theta = np.pi / 60   # angular resolution in radians of the Hough grid
    threshold = 400    # minimum number of votes (intersections in Hough grid cell)
    min_line_length = 50  # minimum number of pixels making up a line
    max_line_gap = 25     # maximum gap in pixels between connectable line segments
    line_image = np.copy(blur_gray) * 0  # creating a blank to draw lines on
  
    lines = []
    
    # Run Hough on edge detected image
    # Output "lines" is an array containing endpoints of detected line segments
    lines = cv2.HoughLinesP(edges, rho, theta, threshold, np.array([]),
                    min_line_length, max_line_gap)
    count=0
    
    #print(lines is None)
    
    if lines is None:
        continue
    #print(lines)
    for line in lines:
        count+=1
        for x1,y1,x2,y2 in line:
            cv2.line(line_image,(x1,y1),(x2,y2),(255,0,0),5)
            # Draw the lines on the  image
    
    lines_edges = cv2.addWeighted(blur_gray, 0.8, line_image, 1, 0)
    lines = lines.reshape(count,4)
    slope1=[]
    slope2=[]
    for i in range(count):
        x_coordinate = []
        y_coordinate = []
        for j in range(4):
            if j%2:
                y_coordinate.append(lines[i][j])
            else:
                x_coordinate.append(lines[i][j])
        result=linregress(x_coordinate,y_coordinate)
        result=np.degrees(np.arctan(result[0]))
        #print(result)
        if result>=0:
            slope1.append(result)
        else:
            slope2.append(result)
        slope1=[slope1 for slope1 in slope1 if str(slope1) != 'nan']
        slope2=[slope2 for slope2 in slope2 if str(slope2) != 'nan']
        #print('slope1=',slope1)
        #print('slope2=',slope2)
        s1=sum(slope1)/len(slope1)
        s2=sum(slope2)/len(slope2)
        if len(slope1)>0:
            s1=sum(slope1)/len(slope1)
            #print('average1=',s1)
          
        if len(slope2)>0:
            s2=sum(slope2)/len(slope2)
            #print('average2=',s2)
        final1=[]
        final2=[]
        if(s1<45):
            final1.append(s1)
            for i in range(len(final1)):
                final1= [x for x in final1 if x != max]
                print('final1=',final1)
          
        if(abs(s2)<45):
            final2.append(s2)
            for i in range(len(final2)):
                final2= [x for x in final2 if x != max]
                print('final2=',final2)
          
        
    #out.write(lines_edges)
    cv2.imshow('lines_edges',lines_edges)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cap.release()
cv2.destroyAllWindows()
sys.exit()


### PCA9685
1. 將 motor control 以 array 傳控制訊號 (kgf)
2. 將 motor control node 包成 class [github](https://github.com/NCTU-AUV/Controller/commit/4dddec15b6373e20a370aa9e72643258fcdbd3e3)
3. 利用 pyqtgraph 視覺化 pitch roll
4. 如果要更改 pca9685 的頻率 要先改回睡眠模式 [網站](http://blog.ittraining.com.tw/2015/07/raspberry-pi2-python-i2c-16-pwm-pca9685.html)的頻率公式有錯
**正確:**
5. [相關細節](https://hackmd.io/yRG0nUkNSgiBiFhXCQy25w?both#PyQt-amp-PyQtGraph)

## 9/2
- PID control 可以在螢幕上跑了 泳池來要去調參數
- Yaw 的地板版本完成即時

## 9/3
:::danger
# 水聽大爆發 :+1: :fire: :dancers: :baby:
- 感謝交大第一顏值擔當 aka 水聽組扛壩子 -- 梁育騰
- 直接拿資料成功
- 肉眼可以看出波形前後
- 麥克風2 (Due板A1) 比較強勢
- 大家回去辨識資料看看
- [FFT & Amplifier & Hilbert](https://wizardforcel.gitbooks.io/hyry-studio-scipy/content/20.html)
:::
-------
## 9/4
- FSM 第一版完成
- 壓力計換算測試

## Detail
想說為了排版方便，就把雜亂的東東丟過來

### PyQt & PyQtGraph
1. https://www.learnpyqt.com/courses/graphics-plotting/plotting-pyqtgraph/
2. https://www.cnblogs.com/linyfeng/p/12239856.html

#### 8/26 pid code
https://www-users.cs.york.ac.uk/~mjf/perpetual_pi/Python/pid.py

### xlxs with python
To read T200 data sheet

from openpyxl import load_workbook

wb = load_workbook('T200.xlsx')
sheet_16v = wb.get_sheet_by_name('16 V')

# col_force = [col.value for col in sheet_16v['F']]
# for val in col_force:
#     print(val, end=', ')

col_signal = [col.value for col in sheet_16v['H']]
for val in col_signal:
    print(val, end=', ')

#

### 壓力計

#include <Wire.h>
#include "MS5837.h"

MS5837 sensor;

void setup() {
  
  Serial.begin(9600);
  
  Serial.println("Starting");
  
  Wire.begin();
  sensor.setModel(MS5837::MS5837_30BA);
  sensor.setFluidDensity(997); // kg/m^3 (freshwater, 1029 for seawater)
}
void loop() {
  sensor.read();
  Serial.print(5.26*(sensor.depth()-196)+1.584); 
  delay(10);
}

## 12/6 檢討
1. NUC 試用
2. Rpi 使用PWM __ **(connect arduino*2)**
3. TX2 視覺

### 配重：
1. 把白色板子拔掉
2. 算浮心
3. 想辦法把密度變成0.9

### 購買：
1. 鉛塊
2. 銅柱
3. 穩壓 (switch 和 NUC 和 TX2)
5. 鰭片
6. 散熱膏
7. KillButtom

### 馬達：
1. 重新焊接

### 鏡頭:
1. train 泥庫