Пример #1
0
import cv2
import numpy as np
from tensorflow.keras.models import load_model

import WebcamModule as wM
import MotorModule as mM

#######################################
steeringSen = 0.70  # Steering Sensitivity
maxThrottle = 0.22  # Forward Speed %
motor = mM.Motor(2, 3, 4, 17, 22, 27)  # Pin Numbers
model = load_model('/home/pi/Desktop/My Files/RpiRobot/model_V1.h5')
######################################


def preProcess(img):
    img = img[54:120, :, :]
    img = cv2.cvtColor(img, cv2.COLOR_RGB2YUV)
    img = cv2.GaussianBlur(img, (3, 3), 0)
    img = cv2.resize(img, (200, 66))
    img = img / 255
    return img


while True:

    img = wM.getImg(True, size=[240, 120])
    img = np.asarray(img)
    img = preProcess(img)
    img = np.array([img])
    steering = float(model.predict(img))
import WebcamModule as wM
import DataCollectionModule as dcM
import JoyStickModule as jsM
import MotorModule as mM
import cv2
from time import sleep


maxThrottle = 0.25
motor = mM.Motor(2, 3, 4, 17, 22, 27)

record = 0
while True:
    joyVal = jsM.getJS()
    #print(joyVal)
    steering = joyVal['axis1']
    throttle = joyVal['o']*maxThrottle
    if joyVal['share'] == 1:
        if record ==0: print('Recording Started ...')
        record +=1
        sleep(0.300)
    if record == 1:
        img = wM.getImg(True,size=[240,120])
        dcM.saveData(img,steering)
    elif record == 2:
        dcM.saveLog()
        record = 0

    motor.move(throttle,-steering)
    cv2.waitKey(1)
Пример #3
0
import cv2
import os
import numpy as np

import CameraModule as cm
import MotorModule as mt
from TfLiteInterpreter import Interpreter

#### Configuration ####################################
steering_sensitivity = 1.9
max_throttle = 0.35
motor = mt.Motor(18, 11, 13, 15, 16, 22)
tflite_modelpath = 'model_v1.tflite'
#######################################################

def preprocess(img):
    img = img[174:,:,:]
    img = cv2.cvtColor(img, cv2.COLOR_BGR2YUV)
    img = cv2.GaussianBlur(img, (3,3), 0)
    img = cv2.resize(img, (200, 66))
    img = img / 255
    return img


try:
    interpreter = Interpreter(tflite_modelpath)

    while True:
        img = cm.get_img(False, size=[480,240])
        img = preprocess(img)
        img = np.array([img], dtype=np.float32)