Al Kari alkari

Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12 (updated October 5, 2017)

These instructions were inspired by Mistobaan's gist, ageitgey's gist, and mattiasarro's tutorial.

Background

I always encountered the following warnings when running my scripts using the precompiled TensorFlow Python package:

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] Th

Install dlib and face_recognition on a Raspberry Pi

Instructions tested with a Raspberry Pi 2 with an 8GB memory card. Probably also works fine on a Raspberry Pi 3.

Steps

Download the latest Raspbian Jessie Light image. Earlier versions of Raspbian won't work.

Write it to a memory card using Etcher, put the memory card in the RPi and boot it up.

How to install dlib v19.9 or newer (w/ python bindings) from github on macOS and Ubuntu

Pre-reqs:

Have Python 3 installed. On macOS, this could be installed from homebrew or even via standard Python 3.6 downloaded installer from https://www.python.org/download. On Linux, just use your package manager.
On macOS:
- Install XCode from the Mac App Store (or install the XCode command line utils).
- Have homebrew installed
On Linux:

Build tensorflow on OSX with NVIDIA CUDA support (GPU acceleration)

These instructions are based on Mistobaan's gist but expanded and updated to work with the latest tensorflow OSX CUDA PR.

	import UIKit
	import AVFoundation

	class Camera: NSObject {
	var captureSession: AVCaptureSession?
	var currentCameraPosition: CameraPosition?
	var frontCamera: AVCaptureDevice?
	var frontCameraInput: AVCaptureDeviceInput?
	var photoOutput: AVCapturePhotoOutput?
	var rearCamera: AVCaptureDevice?

	# Make sure you grab the latest version
	curl -OL https://github.com/google/protobuf/releases/download/v3.5.1/protoc-3.5.1-linux-x86_64.zip

	# Unzip
	unzip protoc-3.5.1-linux-x86_64.zip -d protoc3

	# Move protoc to /usr/local/bin/
	sudo mv protoc3/bin/* /usr/local/bin/

	# Move protoc3/include to /usr/local/include/

	List of ImageNet class numbers and names as used in Keras' pre-trained models.

	Extracted from https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json

	0, tench
	1, goldfish
	2, great_white_shark
	3, tiger_shark
	4, hammerhead
	5, electric_ray

	(function() {

	var width = 320;
	var height = 0;
	var streaming = false;

	var video = null;
	var canvas = null;
	var photo = null;
	var startbutton = null;

	#!/usr/bin/env python
	# Note, updated version of
	# https://github.com/ipython/ipython-in-depth/blob/master/tools/nbmerge.py
	"""
	usage:

	python nbmerge.py A.ipynb B.ipynb C.ipynb > merged.ipynb
	"""

	import io