START_NUMBER = 60
# what to end at
hm_data = 111
# use a previous model to begin?
START_FRESH = False
WIDTH = 160
HEIGHT = 120
LR = 1e-3
EPOCHS = 1
MODEL_NAME = ''
EXISTING_MODEL_NAME = ''
model = alexnet2(WIDTH, HEIGHT, LR, output=9)
if not START_FRESH:
model.load(EXISTING_MODEL_NAME)
for i in range(EPOCHS):
data_order = [i for i in range(START_NUMBER, hm_data + 1)]
shuffle(data_order)
for i in data_order:
train_data = np.load('training_data.npy'.format(i))
df = pd.DataFrame(train_data)
df = df.iloc[np.random.permutation(len(df))]
train_data = df.values.tolist()
train = train_data[:-100]
from alexnet import alexnet, alexnet2
import numpy as np
import os
import tensorflow as tf
data = np.load('training_data_after_Canny.npy', allow_pickle=True)
model = alexnet2(152, 104, 0.5, 3)
model.predict(data[0][0])
print(1)
START_NUMBER = 60
# what to end at
hm_data = 111
# use a previous model to begin?
START_FRESH = False
WIDTH = 160
HEIGHT = 120
LR = 1e-3
EPOCHS = 1
MODEL_NAME = ''
EXISTING_MODEL_NAME = ''
model = alexnet2(WIDTH, HEIGHT, LR, output=9)
if not START_FRESH:
model.load(EXISTING_MODEL_NAME)
for i in range(EPOCHS):
data_order = [i for i in range(START_NUMBER,hm_data+1)]
shuffle(data_order)
for i in data_order:
train_data = np.load('training_data-{}.npy'.format(i))
df = pd.DataFrame(train_data)
df = df.iloc[np.random.permutation(len(df))]
train_data = df.values.tolist()
train = train_data[:-100]
#ReleaseKey(A)
time.sleep(t_time)
ReleaseKey(A)
def right():
PressKey(W)
PressKey(D)
ReleaseKey(A)
#ReleaseKey(W)
#ReleaseKey(D)
time.sleep(t_time)
ReleaseKey(D)
model = alexnet2(WIDTH, HEIGHT, LR)
model.load(MODEL_NAME)
def region_of_interest(img, vertices):
mask = np.zeros_like(img)
match_mask_color = 255
cv2.fillPoly(mask, vertices, match_mask_color)
masked_image = cv2.bitwise_and(img, mask)
return masked_image
def main():
last_time = time.time()
region_of_interest_vertices = [(0, 480), (0, 294), (640, 294), (640, 480)]
for i in list(range(4))[::-1]:
def forward_right():
PressKey(W)
PressKey(D)
ReleaseKey(A)
def no_keys():
PressKey(W)
ReleaseKey(A)
ReleaseKey(S)
ReleaseKey(D)
model = alexnet2(width, height, 6)
model.load(model_name)
def main():
last_time = time()
for i in range(1, 4):
print(4 - i)
sleep(1)
paused = False
while (True):
if not paused:
screen = takeScreenShot(region=(0, 30, 800, 630))
print('loop took {} seconds'.format(time() - last_time))
from random import shuffle
import pandas as pd
import tflearn, os
# what to start at
START_NUMBER = 60
# what to end at
hm_data = 111
w = 160
h = 120
modelName = 'GTA5-TestModel-70k-data.model'
trainingDataName = 'trainingData.npy'
model = alexnet2(w, h, 6)
if os.path.isfile(modelName):
print("File exists")
model.load(modelName)
epochs = 10
for i in range(epochs):
data_order = [i for i in range(START_NUMBER, hm_data + 1)]
shuffle(data_order)
for i in data_order:
trainData = np.load(trainingDataName)
df = pd.DataFrame(trainData)
df = df.iloc[np.random.permutation(len(df))]