tarun tarun-ssharma

model = tf.keras.models.Sequential([
  tf.keras.layers.Flatten(input_shape=(28, 28)),
  tf.keras.layers.Dense(128, activation='relu'),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',

Using an Access Token for the first time

Follow the instructions on Github to Create an Access Token in Github

Configure Git to use the osxkeychain

By default, git credentials are not cached so you need to tell Git if you want to avoid having to provide them each time Github requires you to authenticate. On Mac, Git comes with an “osxkeychain” mode, which caches credentials in the secure keychain that’s attached to your system account.

You can tell Git you want to store credentials in the osxkeychain by running the following:-

To remove a submodule you need to:

Delete the relevant section from the .gitmodules file.
Stage the .gitmodules changes git add .gitmodules
Delete the relevant section from .git/config.
Run git rm --cached path_to_submodule (no trailing slash).
Run rm -rf .git/modules/path_to_submodule (no trailing slash).
Commit git commit -m "Removed submodule "
Delete the now untracked submodule files rm -rf path_to_submodule

How To Work With Multiple Github Accounts on a single Machine

Let suppose I have two github accounts, https://github.com/rahul-office and https://github.com/rahul-personal. Now i want to setup my mac to easily talk to both the github accounts.

NOTE: This logic can be extended to more than two accounts also. :)

The setup can be done in 5 easy steps:

Steps:

Step 1 : Create SSH keys for all accounts
Step 2 : Add SSH keys to SSH Agent

	"""
	author: Timothy C. Arlen
	date: 28 Feb 2018

	revised by: Sadjad Asghari Esfeden
	date: 10 Sep 2018

	Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific
	image Ids. Usage:

	# TFLite quantized inference example
	#
	# Based on:
	# https://www.tensorflow.org/lite/performance/post_training_integer_quant
	# https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/Tensor.QuantizationParams

	import numpy as np
	import tensorflow as tf

	# Location of tflite model file (float32 or int8 quantized)

	import cv2
	import time

	CONFIDENCE_THRESHOLD = 0.2
	NMS_THRESHOLD = 0.4
	COLORS = [(0, 255, 255), (255, 255, 0), (0, 255, 0), (255, 0, 0)]

	class_names = []
	with open("classes.txt", "r") as f:
	class_names = [cname.strip() for cname in f.readlines()]

	# -- coding: utf-8 --
	import cv2
	import tensorflow as tf
	import numpy as np

	# https://www.tensorflow.org/lite/guide/hosted_models
	# http://storage.googleapis.com/download.tensorflow.org/models/tflite/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip


	def detect_from_camera():

	# echo "blacklist nouveau" \| sudo tee -a /etc/modprobe.d/blacklist-nouveau.conf > /dev/null
	# echo "options nouveau modeset=0" \| sudo tee -a /etc/modprobe.d/blacklist-nouveau.conf > /dev/null
	# sudo update-initramfs -u

	sudo apt update
	sudo apt -y install build-essential

	sudo apt update
	sudo apt -y install linux-headers-$(uname -r)

	wget --no-check-certificate --content-disposition https://github.com/joyent/node/tarball/v0.7.1
	# --no-check-cerftificate was necessary for me to have wget not puke about https
	curl -LJO https://github.com/joyent/node/tarball/v0.7.1