detection

I want to know how to detect GPS HardWare in present in Iphone or not Even though you can not determine this using the SDK, you may exploit your knowledge of current models. If you limit yourself to iPhone 3G, iPhone 3GS and iPod Touch 2nd generation (I do not personally support older iPhone edge or iPod Touch 1st generation), then you already know that the iPhone models ship with a real AGPS unit while the iPod Touch 2nd generation can use - if and when available - geotagged wifi hot spots. You may then use the following method to determine the model you are running on: - (NSString *)

The aim for me is to have a mobile website (for mobiles and tablets) and a responsive desktop website, built on Wordpress. I want the easiest way to implement fool proof device detection. The mobile website is going to have a lot of features that are only really going to benefit touch devices and will be custom designed for mobiles and tablets. The desktop site will be completely different (with same pages but with additional content) and will be fully responsive just in case any devices slip through the detection. I have this one liner that will detect touch devices and redirect to another

I'm learning about MobileNet thesedays and i'm new to tensorflow. After training with ssd-mobilenet model,i got checkpoint file , .meta file , graph.pbtxt file and so on. When I try to predict with these files, i can't get the output such as box_pred, classs_scores... Then I found predict demo code used .pb file to load graph ,and used "get_tensor_by_name" to get output, but Ｉ don't have .pb file. So, how can I predict an image with .meta and ckpt files ? BTW, here is predict demon main code: import numpy as np import os import six.moves.urllib as urllib import sys import tarfile import

When I check the tensorboard for observing the training performance, there only shows the eval_0 (in blue) result. While it should be a separate train (in orange) and eval (in blue) result as shown in the website of tensorboard ( https://www.tensorflow.org/guide/summaries_and_tensorboard ?). However, I want to compare the model performance on training dataset and eval dataset. So I checked the models/research/object_detection/model_main.py and want to know if I I can get the precision based on the train and eval dataset by set the flag of model_dir to model/eval folder and set the flag of eval