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collect_training_data.py
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collect_training_data.py
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import numpy as np
import cv2
import serial
import pygame
from pygame.locals import *
import socket
import time
import os
class CollectTrainingData(object):
def __init__(self):
self.server_socket = socket.socket()
self.server_socket.bind(('192.168.1.100', 8000))
self.server_socket.listen(0)
# accept a single connection
self.connection = self.server_socket.accept()[0].makefile('rb')
# connect to a seral port
self.ser = serial.Serial('/dev/tty.usbmodem1421', 115200, timeout=1)
self.send_inst = True
# create labels
self.k = np.zeros((4, 4), 'float')
for i in range(4):
self.k[i, i] = 1
self.temp_label = np.zeros((1, 4), 'float')
pygame.init()
self.collect_image()
def collect_image(self):
saved_frame = 0
total_frame = 0
# collect images for training
print 'Start collecting images...'
e1 = cv2.getTickCount()
image_array = np.zeros((1, 38400))
label_array = np.zeros((1, 4), 'float')
# stream video frames one by one
try:
stream_bytes = ' '
frame = 1
while self.send_inst:
stream_bytes += self.connection.read(1024)
first = stream_bytes.find('\xff\xd8')
last = stream_bytes.find('\xff\xd9')
if first != -1 and last != -1:
jpg = stream_bytes[first:last + 2]
stream_bytes = stream_bytes[last + 2:]
image = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8), cv2.CV_LOAD_IMAGE_GRAYSCALE)
# select lower half of the image
roi = image[120:240, :]
# save streamed images
cv2.imwrite('training_images/frame{:>05}.jpg'.format(frame), image)
#cv2.imshow('roi_image', roi)
cv2.imshow('image', image)
# reshape the roi image into one row array
temp_array = roi.reshape(1, 38400).astype(np.float32)
frame += 1
total_frame += 1
# get input from human driver
for event in pygame.event.get():
if event.type == KEYDOWN:
key_input = pygame.key.get_pressed()
# complex orders
if key_input[pygame.K_UP] and key_input[pygame.K_RIGHT]:
print("Forward Right")
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[1]))
saved_frame += 1
self.ser.write(chr(6))
elif key_input[pygame.K_UP] and key_input[pygame.K_LEFT]:
print("Forward Left")
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[0]))
saved_frame += 1
self.ser.write(chr(7))
elif key_input[pygame.K_DOWN] and key_input[pygame.K_RIGHT]:
print("Reverse Right")
self.ser.write(chr(8))
elif key_input[pygame.K_DOWN] and key_input[pygame.K_LEFT]:
print("Reverse Left")
self.ser.write(chr(9))
# simple orders
elif key_input[pygame.K_UP]:
print("Forward")
saved_frame += 1
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[2]))
self.ser.write(chr(1))
elif key_input[pygame.K_DOWN]:
print("Reverse")
saved_frame += 1
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[3]))
self.ser.write(chr(2))
elif key_input[pygame.K_RIGHT]:
print("Right")
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[1]))
saved_frame += 1
self.ser.write(chr(3))
elif key_input[pygame.K_LEFT]:
print("Left")
image_array = np.vstack((image_array, temp_array))
label_array = np.vstack((label_array, self.k[0]))
saved_frame += 1
self.ser.write(chr(4))
elif key_input[pygame.K_x] or key_input[pygame.K_q]:
print 'exit'
self.send_inst = False
self.ser.write(chr(0))
break
elif event.type == pygame.KEYUP:
self.ser.write(chr(0))
# save training images and labels
train = image_array[1:, :]
train_labels = label_array[1:, :]
# save training data as a numpy file
file_name = str(int(time.time()))
directory = "training_data"
if not os.path.exists(directory):
os.makedirs(directory)
try:
np.savez(directory + '/' + file_name + '.npz', train=train, train_labels=train_labels)
except IOError as e:
print(e)
e2 = cv2.getTickCount()
# calculate streaming duration
time0 = (e2 - e1) / cv2.getTickFrequency()
print 'Streaming duration:', time0
print(train.shape)
print(train_labels.shape)
print 'Total frame:', total_frame
print 'Saved frame:', saved_frame
print 'Dropped frame', total_frame - saved_frame
finally:
self.connection.close()
self.server_socket.close()
if __name__ == '__main__':
CollectTrainingData()