# you need to install websockets before you use this
print('\n'*50)
import asyncio
import websockets
from auto_everything.base import IO
io = IO()
import json
from opencv import MyOpencv
myopencv = MyOpencv()
async def hello(websocket, path):
global one_frame_of_data
while 1:
data = await websocket.recv()
if isinstance(data, str):
json_data = json.loads(data)
print(json_data)
print('\n'*2)
elif isinstance(data, bytes):
myopencv.show(data)
start_server = websockets.serve(hello, 'localhost', 8000)
asyncio.get_event_loop().run_until_complete(start_server)
#!/usr/bin/env /usr/bin/python3
from auto_everything.terminal import Terminal
from auto_everything.disk import Disk
from auto_everything.base import IO
from auto_everything.base import Python
import json
t = Terminal()
disk = Disk()
io = IO()
py = Python()
def seperate():
print()
print("-------")
print()
DEVICE = "/dev/ttyUSB0"
PRE_COMMAND = f"ampy -p {DEVICE} "
LS = PRE_COMMAND + "ls"
DELETE = PRE_COMMAND + "rm "
PUT = PRE_COMMAND + "put "
micropython_files = [
name.strip("/") for name in t.run_command(LS).split("\n")
if name.strip() != "" and name[-3:] == ".py"
]
print(micropython_files)
if len(micropython_files) == 0:
exit()
from model import generate_model
import tensorflow as tf
import os
import numpy as np
from random import randint
from nes_py.wrappers import JoypadSpace
import gym_super_mario_bros
from gym_super_mario_bros.actions import SIMPLE_MOVEMENT
import time
import random
from auto_everything.base import IO
io = IO()
env = gym_super_mario_bros.make('SuperMarioBros-v2')
env = JoypadSpace(env, SIMPLE_MOVEMENT)
model_file_path = './nn_model.HDF5'
final_model_file_path = './final_nn_model.HDF5'
if os.path.exists(model_file_path):
model = tf.keras.models.load_model(model_file_path)
else:
model = generate_model()
# env.action_space.sample() = numbers, for example, 0,1,2,3...
# state = RGB of raw picture; is a numpy array with shape (240, 256, 3)
# reward = int; for example, 0, 1 ,2, ...
# done = False or True
# info = {'coins': 0, 'flag_get': False, 'life': 3, 'score': 0, 'stage': 1, 'status': 'small', 'time': 400, 'world': 1, 'x_pos': 40}
done = True
last_state = None
from auto_everything.base import IO
io = IO()
import os
import json
files = os.listdir("../data")
files = [file for file in files if '.json' in file]
item_list = []
for index, file in enumerate(files):
file = file.replace(".json", "")
item_list.append({'index': index, 'label_name': file})
print(index, file)
start = """
export const motion_classes = {
"""
end = "}"
final_js = start
for item in item_list:
final_js += '{index}: "{name}",'.format(index=item['index'],
name=item['label_name']) + '\n'
final_js += end
io.write('../js/motion_classes.js', final_js)
from model import generate_model
import tensorflow as tf
import os
import numpy as np
import time
from random import randint
from nes_py.wrappers import JoypadSpace
import gym_super_mario_bros
from gym_super_mario_bros.actions import COMPLEX_MOVEMENT
from auto_everything.base import IO
io = IO()
env = gym_super_mario_bros.make('SuperMarioBros-v2')
env = JoypadSpace(env, COMPLEX_MOVEMENT)
model_file_path = './nn_model.HDF5'
final_model_file_path = './final_nn_model.HDF5'
if os.path.exists(model_file_path):
model = tf.keras.models.load_model(model_file_path)
else:
model = generate_model()
# env.action_space.sample() = numbers, for example, 0,1,2,3...
# state = RGB of raw picture; is a numpy array with shape (240, 256, 3)
# reward = int; for example, 0, 1 ,2, ...
# done = False or True
# info = {'coins': 0, 'flag_get': False, 'life': 3, 'score': 0, 'stage': 1, 'status': 'small', 'time': 400, 'world': 1, 'x_pos': 40}
identity = np.identity(
#!/usr/bin/env /usr/bin/python3
#!/usr/bin/env /usr/bin/python3
from auto_everything.base import Python, Terminal, IO
py = Python()
t = Terminal()
io_ = IO()
class Tools():
def build(self):
t.run('yarn build')
content = io_.read("./build/index.html")
content = content.replace(
"<title>React App</title>", """
<title>yingshaoxo | 技术宅</title>
<meta name="author" content="yingshaoxo" />
<meta name="description" content="yingshaoxo, born in 1998, love IT. Want to find out all those mysteries in this universe, especially how human thinks. So I embrace AI." />
<meta name="keywords" content="yingshaoxo, Python, Javascript, C++" />
""".replace("\n", ""))
io_.write("./build/index.html", content)
py.make_it_runnable()
py.fire(Tools)
import eventlet
eventlet.monkey_patch()
from king_chat import Server
server = Server(ip="0.0.0.0", port=5920)
import json
import os
from auto_everything.base import IO
io = IO()
from flask import Flask, render_template,redirect
from flask_socketio import SocketIO, emit
# make sure static folder is the react build folder, and static path is the root, so static_url_path = ''
app = Flask(__name__, template_folder='../front-end_app/build', static_url_path='', static_folder='../front-end_app/build')
app.config['SECRET_KEY'] = 'yingshaoxo is the king'
socketio = SocketIO(app)
msgs = []
temp_json_file = "msgs.json"
if not os.path.exists(temp_json_file):
io.write(temp_json_file, json.dumps([]))
@server.on_received
def handle(protocol, text):
#protocol.send_to_all_except_sender(text)
from auto_everything.base import IO
io = IO()
import os
import json
files = os.listdir("../data")
files = [file for file in files if '.json' in file]
item_list = []
for index, file in enumerate(files):
file = file.replace(".json", "")
item_list.append({'index': index, 'label_name': file})
print(index, file)
start = """
export const looking_classes = {
"""
end = "}"
final_js = start
for item in item_list:
final_js += '{index}: "{name}",'.format(index=item['index'],
name=item['label_name']) + '\n'
final_js += end
io.write('../js/looking_classes.js', final_js)
import os
from auto_everything.base import IO
io = IO()
import json
from pprint import pprint
import numpy as np
files = os.listdir("../data")
files = [file for file in files if '.json' in file]
global x, y
for index, file in enumerate(files):
# get x
xx = json.loads(io.read("../data/{name}".format(name=file)))
xx = np.array(xx)
print(xx.shape)
# get y
#yy = np.zeros(xx.shape[0])
yy = np.full(xx.shape[0], index)
if index == 0:
x = xx
y = yy
else:
x = np.append(x, xx, axis=0)
y = np.append(y, yy, axis=0)
from auto_everything.base import IO
io = IO()
import os
import json
files = os.listdir("../data")
files = [file for file in files if '.json' in file]
item_list = []
for index, file in enumerate(files):
file = file.replace(".json", "")
item_list.append({'index': index, 'label_name': file})
print(index, file)
start = """
export const pose_classes = {
"""
end = "}"
final_js = start
for item in item_list:
final_js += '{index}: "{name}",'.format(index=item['index'],
name=item['label_name']) + '\n'
final_js += end
io.write('../js/pose_classes.js', final_js)
