retinal | Retinal is a Serverless AWS Lambda service | Serverless library
kandi X-RAY | retinal Summary
kandi X-RAY | retinal Summary
A tool to take images uploaded to an S3 bucket and produce one or more images of varying sizes, optimizations and other operations all controlled from a simple configuration file. It does this by creating an AWS Lambda function with the help of the Serverless Framework.
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QUESTION
** Updated question with MWE
I am currently using a custom background template image and at the end of my presentation, I want to display the citations that I used. However, I cannot seem to figure out how to eliminate the black lines around the top, left & right side of the frame title "References".
Here is the text used to create the background template from a PDF
...ANSWER
Answered 2020-Oct-25 at 08:49Natbib normally start a new section for the references, but starting a new section inside a frame is not a good idea. You can avoid the problem, by redefining the \bibsection
macro:
QUESTION
How to add new value not in chosen.
I have set 'no_results_text' as tag. its working.
$('#secondary_diagnosis').chosen({no_results_text: '
Save as New '});
This is my Code:
But if i want add new value in half of exiting value, then 'no_results_text' not showing. i need solution for call my predefined function add_new_diagnosis()
.
How Can i put tags on the
chosen-search-input
?
Current code:
...ANSWER
Answered 2020-Oct-02 at 04:27You should try select2 jquery plugin instead of chosenJS.
HTML:
QUESTION
I created a DataFrame from JSON file, in which values are like
...ANSWER
Answered 2020-May-13 at 19:46I'm still not sure if I fully understand your output, but here's a crack at it with demo code:
QUESTION
ANSWER
Answered 2020-May-07 at 11:48You need to identify larger structures. Ideally you need a structure size about 1/4 of the radius of the optic disk to balance results and processing time (experiment with larger sizes until acceptable).
Or you could downsample the image (reduce the resolution and make the picture smaller), which is more or less the same thing, even if you lose precision on the optic disk borders.
QUESTION
I'm trying to import txt data into R; however, due to the txt file's unique formatting, I'm unsure of how to do this. I definitely feel that the issue is related to the fact that the txt file was formatted to line up columns with column names; however, as it's a text file, this was done with a variety of spaces. For example:
...ANSWER
Answered 2019-Nov-20 at 18:07Each field has a fixed width. Therefore, you can use the function read.fwf
to read the file.
The following code reads the input file (assuming the file has only the rows, without the headers)
QUESTION
I have to identify a retinal disease with CNN. I have 1400 images, 700 each class. My classes are (0 - no PDR) and (1 - PDR). I'm trying to make a model to identify if an input retina have the disease in level 4 or not.
I'm making a follow manipulation with my images and rezise all to 256x256:
...ANSWER
Answered 2019-Sep-20 at 18:17It seems you having issues with overfitting. I have kind of a personal dilemma in here whether this is off-topic or not because the approach one can give it's somewhat opinion-based, but here I go:
First off, if you need to regularize an overfitting network, you want to use dropout
starting at 0.25
and checking if that improves the model. Data augmentation
is a must when dealing with overfitting, together with batch normalization
(which you are applying).
If this still not solves your overfitting problems, then you should try working on your network architecture to tweak it in order to make it generalize better. Did you check a simple of the inputs being used for train and test?
TLDR: Try dropout and data augmentation, if it doesn't work and your data is correct, you might have to work on improving the architecture to make a better generalizing model.
EDIT: The consensus on approaching this kind of models is to have it overfit at first, with a decent accuracy and then work towards generalizing it without losing accuracy if possible.
QUESTION
ANSWER
Answered 2019-Jan-29 at 08:27It seems to be enough to give the tabs a fixed height and let the content overflow automagically:
QUESTION
I have been scouring the internet for around 2 days now and I can't find anything about an issue. I am facing with extra space on the LEFT and RIGHT side of images in Outlook desktop.
The extra space, affects the ability of my table/columns to be displayed side by side. If I shorten the width of any cell/row/table to the exact width of that space (circled in red in image) they suddenly pop in side by side. It is this particular little space I can't figure out how to remove. It is like there is a default value set somewhere on something I am unaware of.
Sorry about some images not being uploaded anywhere, these ones weren't really important.
2 How it appears in every other email client. 3 How it is appearing in outlook only.
...ANSWER
Answered 2018-Dec-13 at 02:37According to my test and search, it not img's reason, might be table.
You could refer to the below code:
QUESTION
I am uploading a big file into BigQuery, because it is too slow to operate on my own PC.
bq --location=EU load --field_delimiter='\t' --skip_leading_rows=1 --source_format=CSV single_cells.retinal_bipolar gs://single_cells/retinal-bipolar-neuron-drop-seq/exp_matrix.txt ./schema.json
However, I got an error:
BigQuery error in load operation: Too many total leaf fields: 27500
Indeed, the data has 27500 columns; doesn't BigQuery allow this?
...ANSWER
Answered 2018-Aug-14 at 18:19The Maximum columns per table value is 10,000 which means that the error message was thrown since the load job exceeded the maximum number of fields allowed in the schema.
Based on this, an available workaround is to split the table up into smaller tables in order to reduce the number of fields contained; In this way, you will be able to avoid this issue.
QUESTION
This is the image i used. (retinal vessel, DRIVE database)
first, It through a pre-processing process. The pre-processing process is as follows.
gaussian filter is applied to remove noise. (and plot BGR histogram)
...
ANSWER
Answered 2018-Feb-05 at 08:08use circle hough transform to detect the big circle, then force the pixels outside the big circle zero, then you can remove the ring.
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