Okay so my assignment is for an engineering project and I have talked to my teacher many times but without much success. the code reads data that comes from a rotary encoder in a text file. The question I have is how do I make two sets of arrays with age and gender and link it to each text file thats read in. For example the first text file comes from a girl that is 10; that spun a crank and output data to a text file. How do i code so that someway i can assign the first text file to an age and gender? Heres my code so far any help is appreciated.
%% ME 208 Project Group 21
clear; close all; clc;
%Constants
dt=.1;
%Translate Data
mass = 10; %values are in units of Kilograms
radius = 1; %values are in units of meters
inertia = mass*radius^(2);
for ii=1:2
%File Name Variable
filename=['sub_' num2str(ii) '.txt'];
%Data is Collected
Data1=dlmread(filename,'\t',0,0);
%Times for data
t1=dt:dt:length(Data1)*dt;
%Vel
[ang_vel1, ang_acc1]=dxdt_d2xdt2(Data1,2,dt);
torq1 = inertia*ang_acc1;
%Calculations of parameters
meanrt1(ii) = rms(torq1);
maxrt1(ii) = max(torq1);
end
%Plot
figure(1);plot(t1,torq1,t2,torq2); grid minor;
Related
I have a problem loading data from text file in Octave.
My text file looks like this:
# Created by Octave 5.2.0, Wed May 05 16:07:02 2021 GMT <unknown#DESKTOP-HEVT6O6>
# name: x
# type: matrix
# rows: 1
# columns: 3600
4.8899999999999997 4.9000000000000004 4.9000000000000004 4.9100000000000001 4.9299999999999997 4.9249999999999998 ...
I need to load those float numbers in one matrix and plot them in time domain.
My code so far:
fs = 360;
Ts = 1/fs;
d = fileread('ecg.txt');
data = regexp(d(1,136:62328),' ','split');
data = str2double(data);
ed = length(data);
t = linspace(0,Ts,ed - 1);
figure(1)
plot(t,data(1,2:ed))
So My question is if there is another way to do it or if there is a better way to do it.
Your file is in Octave’s text data format. This is the default file format when saving variables to file with save. That is, that text file was saved in Octave using save ecg.txt x. The Octave command load ecg.txt will load the file, and re-create the x variable just like it was when it was saved.
Thus, to plot your data, just do
load ecg.txt
plot(x)
I'm working on a network using triplet mining for training. In order to make it work properly, I need my batches to contain several images of the same class. The problem I'm currently facing is that I have 751 classes, for a total of 12,937 pictures, and a batch size of 48 pictures. When shuffling the dataset using the command below, the odds to get pictures from the same class are really low, making the triplet mining inefficient.
dataset = dataset.shuffle(12937)
What I would need instead is a way of generating batches that contain a specific number of pictures for every class represented in this batch. As an example, let's say here that I want 12 classes per batch, there would be 4 pictures for each of them.
Another problem I'm facing is how would I shuffle this dataset at the end of every epoch so that I can have different batches that still follow the condition fixed above, that is 12 classes, 4 pictures for each one of them?
Is there any proper way to do it? I can't really find one. Please let me know if I'm unclear, and if you need further details.
================ EDIT ================
I've been trying a few things, and came up with something that would do what I want. The function would be the following:
counter = 0.
# Assuming a format such as (data, label)
def predicate(data, label):
global counter
allowed_labels = tf.constant([counter])
isallowed = tf.equal(allowed_labels, tf.cast(label, tf.float32))
reduced = tf.reduce_sum(tf.cast(isallowed, tf.float32))
counter += 1
return tf.greater(reduced, tf.constant(0.))
##tf.function
def custom_shuffle(train_dataset, batch_size, samples_per_class = 4, iterations_in_epoch = 100, database='market'):
assert batch_size%samples_per_class==0, F'batch size must be a {samples_per_class} multiple.'
if database == 'market':
class_nbr = 751
else:
raise Exception('Unsuported database yet')
all_datasets = [train_dataset.filter(predicate) for _ in range(class_nbr)] # Every element of this array is a dataset of one class
for i in range(iterations_in_epoch):
choice = tf.random.uniform(
shape=(batch_size//samples_per_class,),
minval=0,
maxval=class_nbr,
dtype=tf.dtypes.int64,
) # Which classes will be in batch
choice = tf.data.Dataset.from_tensor_slices(tf.concat([choice for _ in range(4)], axis=0)) # Exactly 4 picture from each class in the batch
batch = tf.data.experimental.choose_from_datasets(all_datasets, choice)
if i==0:
all_batches = batch
else:
all_batches = all_batches.concatenate(batch)
all_batches = all_batches.batch(batch_size)
return all_batches
It does what I want, however the returned dataset is extremely slow to iterate, making modele learning impossible. As per this thread, I understood that I needed to decorate custom_shuffle with #tf.function, as the one commented out. However, when doing so, it raises the following error:
Traceback (most recent call last):
File "training.py", line 137, in <module>
main()
File "training.py", line 80, in main
train_dataset = get_dataset(TRAINING_FILENAMES, IMG_SIZE, BATCH_SIZE, database=database, func_type='train')
File "E:\Morgan\TransReID_TF\tfr_to_dataset.py", line 260, in get_dataset
dataset = custom_shuffle(dataset, batch_size)
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\def_function.py", line 780, in __call__
result = self._call(*args, **kwds)
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\def_function.py", line 846, in _call
return self._concrete_stateful_fn._filtered_call(canon_args, canon_kwds) # pylint: disable=protected-access
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\function.py", line 1843, in _filtered_call
return self._call_flat(
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\function.py", line 1923, in _call_flat
return self._build_call_outputs(self._inference_function.call(
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\function.py", line 545, in call
outputs = execute.execute(
File "D:\Programs\Anaconda3\envs\AlignedReID_TF\lib\site-packages\tensorflow\python\eager\execute.py", line 59, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: No unary variant device copy function found for direction: 1 and Variant type_index: class tensorflow::data::`anonymous namespace'::DatasetVariantWrapper
[[{{node BatchDatasetV2/_206}}]] [Op:__inference_custom_shuffle_11485]
Function call stack:
custom_shuffle
Which I don't understand, and don't see how to fix.
Is there something I'm doing wrong?
PS: I'm aware the lack of minimal code to reproduce this behavior makes it hard to debug, I'll try to provide some as soon as possible.
I need to recognize the text in the bottom left corner on Magic the Gathering paper cards (last design). Here an example:
If the text is like this
I want to retrieve the following text:
198/280 U
M20 EN
(I don't need the card author name - Lake Hurwitz in this example)
What OCR library can I use? I've tried with Tesseract without any tuning but the results are not correct. Any advice or link to a project that already does this stuff?
You can make it with tesseract (3.04.01) by sanitizing your image a bit
like in below code
import numpy as np
import cv2
def prepro(zone, prefix):
filename = 'stackmagic.png'
oriimg = cv2.imread(filename)
#keep the interesting part
(a,b,c,d) = zone
text_zone = oriimg[a:b, c:d]
height, width, depth = text_zone.shape
#resize it to be bigger (so less pixelized)
H = 50
imgScale = H/height
newX,newY = text_zone.shape[1]*imgScale, text_zone.shape[0]*imgScale
newimg = cv2.resize(text_zone,(int(newX),int(newY)))
#binarize it
gray = cv2.cvtColor(newimg, cv2.COLOR_BGR2GRAY)
th, img = cv2.threshold(gray, 130, 255, cv2.THRESH_BINARY);
#erode it
kernel = np.ones((1,1),np.uint8)
erosion = cv2.erode(img,kernel,iterations = 1)
cv2.imwrite(prefix+'_ero.png', erosion)
cv2.imshow("Show by CV2",erosion)
cv2.waitKey(0)
prepro((16,27, 6,130), 'upzone')
prepro((27,36, 6,130), 'downzone')
from your cropped image
you get
the upper part:
and the lower part:
and tesseract does seem to be able to extract
xx$ tesseract upzone_ero.png stdout
198/ 280 U
xx$ tesseract downzone_ero.png stdout
M20 ~ EN Duluu Hun-nu
Notice that we fail to extract Luke, but hopefully you were not interested in him/it :)
There are other tools but that'd be advertising stuff and be subjective..
I need help with matlab using 'strtok' to find an ID in a text file and then read in or manipulate the rest of the row that is contained where that ID is. I also need this function to find (using strtok preferably) all occurrences of that same ID and group them in some way so that I can find averages. On to the sample code:
ID list being input:
(This is the KOIName variable)
010447529
010468501
010481335
010529637
010603247......etc.
File with data format:
(This is the StarData variable)
ID>>>>Values
002141865 3.867144e-03 742.000000 0.001121 16.155089 6.297494 0.001677
002141865 5.429278e-03 1940.000000 0.000477 16.583748 11.945627 0.001622
002141865 4.360715e-03 1897.000000 0.000667 16.863406 13.438383 0.001460
002141865 3.972467e-03 2127.000000 0.000459 16.103060 21.966853 0.001196
002141865 8.542932e-03 2094.000000 0.000421 17.452007 18.067214 0.002490
Do not be mislead by the examples I posted, that first number is repeated for about 15 lines then the ID changes and that goes for an entire set of different ID's, then they are repeated as a whole group again, think [1,2,3],[1,2,3], the main difference is the values trailing the ID which I need to average out in matlab.
My current code is:
function Avg_Koi
N = evalin('base', 'KOIName');
file_1 = evalin('base', 'StarData');
global result;
for i=1:size(N)
[id, values] = strtok(file_1);
result = result(id);
result = result(values)
end
end
Thanks for any assistance.
You let us guess a lot, so I guess you want something like this:
load StarData.txt
IDs = { 010447529;
010468501;
010481335;
010529637;
010603247;
002141865}
L = numel(IDs);
values = cell(L,1);
% Iteration through all arrays and creating an cell array with matrices for every ID
for ii=1:L;
ID = IDs{ii};
ID_first = find(StarData(:,1) == ID,1,'first');
ID_last = find(StarData(:,1) == ID,1,'last');
values{ii} = StarData( ID_first:ID_last , 2:end );
end
When you now access the index ii=6 adressing the ID = 002141865
MatrixOfCertainID6 = values{6};
you get:
0.0038671440 742 0.001121 16.155089 6.2974940 0.001677
0.0054292780 1940 0.000477 16.583748 11.945627 0.001622
0.0043607150 1897 0.000667 16.863406 13.438383 0.001460
0.0039724670 2127 0.000459 16.103060 21.966853 0.001196
0.0085429320 2094 0.000421 17.452007 18.067214 0.002490
... for further calculations.
Is there a way to assign file names to set varibles using a GUI? Say I have 6 file sets which contain 4 colors each (blue, green, nir, red). There are 24 files in total, so i'd need 24 variables. And I want the set varialbes to be something like
blue1
green1
nir1
red1
blue2
green2
nir2
red2
etc...
Currently I'm trying to use GUIDE to creat a custom GUI that will allow the user to select the files they wish and have them assigned to certain variables. I am thinking something along the lines of having 24 popupmenus that are attached to a file directory and allows the user to select which file they want, and then it will assign that file and it's path to a variable (blue1 for example) I also want 24 check boxes to associate with an if statement
Let's say popupmenu1 is associated with the variable blue1 and checkbox1
if checkbox1 == checked
do import
elseif checkbox1 == unchecked
fill with zeros
I have the basic frame of the GUI created, I am just unclear on how to apply the file select and then associate the if statements, etc...
If you know the variable files in advance, it's bad practice (look also here and here) to use string defined variable names like this:
var1name = 'blue';
var2name = 'red';
% etc.
% load data
datablue=rand(4,1);
datared =rand(4,1);
% assign
eval([var1name '1 = datablue(1);']);
eval([var2name '1 = datared (1);']);
% etc.
eval([var1name '2 = datablue(2);']);
eval([var2name '1 = datared (2);']);
% etc
It's much easier and better to just use an ordinary array, given the variable name is not changing or application dependend, which in my example I already have as datablue and datared.
Another option if you'd like user defined variable names is to use an array of structs:
var1name = 'blue';
var2name = 'red';
sample(1).(var1name) = datablue(1);
sample(1).(var2name) = datared (1);
% ...
sample(2).(var1name) = datablue(2);
sample(2).(var2name) = datared (2);
Try some of these out, and only if you have a very good reason, resort to eval!
for k = 1:6
blue(k) = sprintf('blue%d', k);
green(k) = sprintf('green%d', k);
nir(k) = sprintf('nir%d', k);
red(k) = sprintf('red%d', k);
end
This will create the variable names for you. Then you can use assignin (i believe) or eval to set the values to the variable names.