How to unstar all your github stars with API
visit here: https://github.com/settings/tokens
make sure to check repo
scope, it is needed to unstar
import os | |
import torch | |
import argparse | |
from maskrcnn_benchmark.config import cfg | |
from maskrcnn_benchmark.utils.c2_model_loading import load_c2_format | |
def removekey(d, listofkeys): | |
r = dict(d) | |
for key in listofkeys: |
How to unstar all your github stars with API
visit here: https://github.com/settings/tokens
make sure to check repo
scope, it is needed to unstar
import sys | |
import os | |
import cv2 | |
import numpy as np | |
import tensorflow as tf | |
sys.path.append("..") | |
from object_detection.utils import label_map_util |
# Stacked LSTMs | |
# Author: Kyle Kastner | |
# Based on script from /u/siblbombs | |
# License: BSD 3-Clause | |
import tensorflow as tf | |
from tensorflow.models.rnn import rnn | |
from tensorflow.models.rnn.rnn_cell import LSTMCell | |
import numpy as np | |
import time |
#include <cmath> | |
#include <climits> | |
#include <queue> | |
#include <vector> | |
#include <map> | |
#include <cstdlib> | |
#include <fstream> | |
#include <iomanip> | |
#include <iostream> | |
#include <sstream> // istringstream buffer(myString); |
The following recipes are sampled from a trained neural net. You can find the repo to train your own neural net here: https://github.com/karpathy/char-rnn Thanks to Andrej Karpathy for the great code! It's really easy to setup.
The recipes I used for training the char-rnn are from a recipe collection called ffts.com And here is the actual zipped data (uncompressed ~35 MB) I used for training. The ZIP is also archived @ archive.org in case the original links becomes invalid in the future.
##Configuring Ubuntu for using IIT Delhi internet
For details http://www.cc.iitd.ernet.in/ and http://mirror.iitd.ernet.in
Thanks Vibhav Sinha for helping in compiling this
###Contents:
@ CSC230 Spring 2012 -- Treadmill program | |
@ Author: Nicolas Guillemot | |
@ Student ID number: V00695164 | |
@ Global constants for physics | |
@ default value for weight | |
.equ DFT_WEIGHT, 100 @ lbs | |
@ minimum value for weight (see WeightMax for maximum) | |
.equ WEIGHT_MIN, 50 @ lbs | |
@ default value for target speed |