yongjun823

{
    "workbench.colorTheme": "Default Light+",
    "workbench.iconTheme": "material-icon-theme",
    "editor.tokenColorCustomizations": {
        "[Material Theme Lighter]": {
         
        },
        "[Default Light+]": {
            "keywords": "#0000ff"
        }

yongjun823

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Flatten, Dense, Conv2D
from tensorflow.keras.preprocessing.image import ImageDataGenerator

train_datagen = ImageDataGenerator(
        rescale=1./255,
        validation_split=0.15
    )

yongjun823

import os
import time
import copy
from soscon.env import Env
from soscon.status import Status
from soscon.data.observation import Observation

class RobotController():
    LIDAR_DATA_SIZE = 360
    IR_DATA_SIZE = 5

yongjun823

import tensorflow as tf 
import numpy as np
import os
import cv2
import argparse

def read_img(name):
    x = cv2.imread(name, cv2.IMREAD_COLOR)
    x = cv2.cvtColor(x, cv2.COLOR_BGR2RGB)
    return x

yongjun823

import random
import os
from tqdm import tqdm
from PIL import Image, ImageOps
from concurrent.futures import ThreadPoolExecutor

original_path = './original/'
resize_path = './resize/'
data_path = './data/'
pbar = None

yongjun823

import numpy as np


def get_pivot(arr, reverse=False):
    if reverse:
        arr = np.flip(arr, 0)[1:]

    for item in arr:
        if item != 0:
            return item

yongjun823

from PIL import Image, ImageOps, ImageCms
from random import randrange
from tqdm import tqdm
from concurrent.futures import ThreadPoolExecutor
import os
import io 

original_path = 'original'
resize_path = 'resize'
folder_arr = ['0']

yongjun823

import tensorlayer as tl
import tensorflow as tf 
from config import config, log_config
from utils import *

def read_tf_img(path, name):
    temp_string = tf.read_file(path + name)
    temp_decoded = tf.image.decode_image(temp_string, channels=4)
    temp_image = tf.image.per_image_standardization(temp_decoded)

yongjun823

import os
import pprint
import tensorflow as tf
import tensorlayer as tl

if 'COLAB_TPU_ADDR' not in os.environ:
  print('ERROR: Not connected to a TPU runtime; please see the first cell in this notebook for instructions!')
else:
  tpu_address = 'grpc://' + os.environ['COLAB_TPU_ADDR']
  print ('TPU address is', tpu_address)

yongjun823

from PIL import Image, ImageOps
from random import randrange
from tqdm import tqdm
import os

target_size = 448
original_path = 'original'
resize_path = 'resize'
folder_arr = ['1262768']