def get_model(time_len=1):
ch, row, col = camera_format.get_camera_image_dim()
model = Sequential()
model.add(
Lambda(lambda x: x / 127.5 - 1.,
input_shape=(ch, row, col),
output_shape=(ch, row, col)))
model.add(Convolution2D(24, 5, 5, subsample=(2, 2), border_mode="same"))
model.add(ELU())
model.add(Convolution2D(36, 5, 5, subsample=(2, 2), border_mode="same"))
model.add(ELU())
model.add(Convolution2D(48, 3, 3, subsample=(2, 2), border_mode="same"))
model.add(ELU())
model.add(Convolution2D(64, 3, 3, subsample=(2, 2), border_mode="same"))
model.add(Flatten())
model.add(Dropout(.2))
model.add(ELU())
model.add(Dense(512))
model.add(Dropout(.5))
model.add(ELU())
model.add(Dense(256))
model.add(ELU())
model.add(Dense(128))
model.add(ELU())
model.add(Dense(1))
model.compile(optimizer="adam", loss="mse")
return model
import sys
import numpy as np
import h5py
import json
from keras.models import model_from_json
#import matplotlib.pyplot as plt
import time
import asyncore
import json
import socket
from PIL import Image
import pygame
import camera_format
pygame.init()
ch, row, col = camera_format.get_camera_image_dim()
size = (col * 2, row * 2)
pygame.display.set_caption("sdsandbox data monitor")
screen = pygame.display.set_mode(size, pygame.DOUBLEBUF)
camera_surface = pygame.surface.Surface((col, row), 0, 24).convert()
myfont = pygame.font.SysFont("monospace", 15)
def screen_print(x, y, msg, screen):
label = myfont.render(msg, 1, (255, 255, 0))
screen.blit(label, (x, y))
def display_img(img, steering):
img = img.transpose().swapaxes(0, 1)
def prepare(drivinglog, drivingimages, outputpath, prefix, activity):
t = time.ctime(os.path.getmtime(drivinglog))
t = t.replace(' ', '_')
t = t.replace(':', '_')
basename = prefix + t + ".h5"
outfilename = os.path.join(outputpath, "log", basename)
infile = open(drivinglog, "r")
lines = []
for line in infile:
lines.append(line)
infile.close()
print 'gathering images', drivingimages
images = glob.glob(drivingimages)
num_images = len(images)
num_records = len(lines)
if (num_images != num_records):
#use the smaller of the two.
if num_images < num_records:
num_records = num_images
else:
num_images = num_records
images = images[:num_images]
print len(lines), 'steering records'
logf = h5py.File(outfilename, "w")
dse = logf.create_dataset("steering_angle", (num_records, ),
dtype='float64')
dse_speed = logf.create_dataset("speed", (num_records, ), dtype='float64')
iIter = 0
iLine = 0
iRecord = 0
num_lines = len(lines)
log_ids = []
while iLine < num_lines and iRecord < num_records:
tokens = lines[iLine].split(',')
iLine += 1
iRecord += 1
if len(tokens) != 4:
continue
log_activity = tokens[1]
if activity is not None and activity != log_activity:
continue
log_ids.append(int(tokens[0]))
steering = float(tokens[2])
speed = float(tokens[3])
dse[iIter] = np.array([steering])
dse_speed[iIter] = np.array([speed])
iIter += 1
if iIter % 1000 == 0:
print iIter
if activity is not None:
print iIter, 'records found w activity', activity
logf.close()
print 'done with log'
outfilename = os.path.join(outputpath, "camera", basename)
camf = h5py.File(outfilename, "w")
print num_images, 'images'
ch, rows, col = camera_format.get_camera_image_dim()
dse = camf.create_dataset("X", (num_images, ch, rows, col), dtype='uint8')
images.sort()
imgs_by_id = {}
for img_filename in images:
path, name = os.path.split(img_filename)
first_zero = name.find('0')
first_period = name.find('.')
num_string = name[first_zero:first_period]
id = int(num_string)
imgs_by_id[id] = img_filename
iIter = 0
for id in log_ids:
try:
img_filename = imgs_by_id[id]
im = Image.open(img_filename).convert('RGB')
if im.width != col or im.height != rows:
print 'Aborting! image:', img_filename, 'had the wrong dimension:', im.width, im.height, 'expecting', col, rows
#stopping because we are likely to see many of these..
return
imarr = np.array(im).transpose()
dse[iIter] = imarr
except KeyError:
print 'no image for frame', id
iIter = iIter + 1
if iIter % 1000 == 0:
print iIter
camf.close()
print 'done with images'
if activity is not None:
print iIter, 'images found w activity', activity