implementation 'androidx.recyclerview:recyclerview:1.0.0'
android.support.design.widget.TextInputLayout => com.google.android.material.textfield.TextInputLayout
android.support.v7.widget.RecyclerView => androidx.recyclerview.widget.RecyclerView
android.support.v4.widget.SwipeRefreshLayout => androidx.swiperefreshlayout.widget.SwipeRefreshLayout
android.support.v7.widget.Toolbar => androidx.appcompat.widget.Toolbar
##Windows users:
cmder will be refered as console
##Mac Os, Ubuntu and windows users continue here:
homestead utf8_general_ci
| Enterprise: NJVYC-BMHX2-G77MM-4XJMR-6Q8QF | |
| Professional: KBJFW-NXHK6-W4WJM-CRMQB-G3CDH | |
| Keys are generic ones. These are the same from MSDN account. | |
| Product Key : -6Q8QF | |
| Validity : Valid | |
| Product ID : 00369-90000-00000-AA703 | |
| Advanced ID : XXXXX-03699-000-000000-00-1032-9200.0000-0672017 |
| # For Windows users# Note: <> denotes changes to be made | |
| #Create a conda environment | |
| conda create --name <environment-name> python=<version:2.7/3.5> | |
| #To create a requirements.txt file: | |
| conda list #Gives you list of packages used for the environment | |
| conda list -e > requirements.txt #Save all the info about packages to your folder |
| ''' | |
| Extract a known face from a video. | |
| Uses a combination of a deep learning CNN model to batch detect faces | |
| in video frames, or a sequence of images, in GPU with CUDA and HoG to compare | |
| the detected faces with a computed reference set of face encodings. | |
| ''' | |
| from os import path, listdir | |
| from typing import NamedTuple |
| ''' | |
| Extract a known face from a video. | |
| Uses a combination of a deep learning CNN model to batch detect faces | |
| in video frames, or a sequence of images, in GPU with CUDA and HoG to compare | |
| the detected faces with a computed reference set of face encodings. | |
| ''' | |
| from os import path, listdir | |
| from typing import NamedTuple |
| """ | |
| author: Timothy C. Arlen | |
| date: 28 Feb 2018 | |
| Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific | |
| image Ids. Usage: | |
| > python calculate_mean_ap.py | |
| Will display a plot of precision vs recall curves at 10 distinct IoU thresholds as well as output |
| """ | |
| author: Timothy C. Arlen | |
| date: 28 Feb 2018 | |
| Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific | |
| image Ids. Usage: | |
| > python calculate_mean_ap.py | |
| Will display a plot of precision vs recall curves at 10 distinct IoU thresholds as well as output |
| import xml.etree.ElementTree as ET | |
| import os | |
| import json | |
| coco = dict() | |
| coco['images'] = [] | |
| coco['type'] = 'instances' | |
| coco['annotations'] = [] | |
| coco['categories'] = [] |