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# ReachView code is placed under the GPL license. | |
# Written by Egor Fedorov ([email protected]) | |
# Copyright (c) 2015, Emlid Limited | |
# All rights reserved. | |
# If you are interested in using ReachView code as a part of a | |
# closed source project, please contact Emlid Limited ([email protected]). | |
# This file is part of ReachView. |
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from flask import Flask | |
app = Flask(__name__) | |
@app.route("/") | |
def home(): | |
return "resonance" | |
app.run() |
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m = 'tjctf{?????????????????}'.lower() | |
k = 'm???????'.lower() | |
f = [[ord(k[a]) ^ ord(m[a+b]) for a in range(8)] for b in range(0, len(m), len(k))] | |
print("F",f) | |
g = [a for b in f for a in b] | |
print("G",g) | |
h = [[g[a] for a in range(b, 24, 8)] for b in range(8)] | |
print("h",h) | |
i = [[h[b][a] ^ ord(k[a]) for a in range(3)] for b in range(8)] |
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------- FS_Init ------- | |
Current search path: | |
./baseq2/pak0.pak (1000 files) | |
./baseq2 | |
1000 files in PAK files | |
----------------------- | |
Execing default.cfg | |
Unknown command "viewsize" | |
Unknown command "sensitivity" | |
Unknown command "crosshair" |
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import keras | |
from keras.datasets import mnist | |
from keras.models import Sequential | |
from keras.layers import * | |
import numpy as np | |
(x_train, y_train), (x_test, y_test) = mnist.load_data() | |
print(x_train) | |
x_test = np.expand_dims(x_test, -1) | |
x_train = np.expand_dims(x_train, -1) | |
print(x_train) |
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import sys | |
import math | |
import time | |
while True: | |