I am using NVIDIA DIGITS for image classification. After I train my network and I test the model on the test data, I want to save the visualization and statistics that DIGITS can generate in my defined folder. How can I do it?
For example how can I save each image square of the following image separately in a folder I specify in the program written for this part??
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Due the Hard Failure I lost the separated photos. The I recovered them using image recovery. But now all the images are in one folder. Those images may be over 500 in the same one folder.
The images have customized names also.
The images are not in the same size also.
The images are not in same dimension also.
I am unable to cluster them and separate them in to a new folder as manually and time consuming. So, is there any online solution or software to automatically cluster them and move them into a folder?
For example :
Image set 1 :
Image set 2 :
Image set 3 :
In the above set of pictures, every image has the same background. So those images should be clustered as one and put them in a folder.
As like this, is there any solution or API level solution to simplify the manual works?
If they are JPEG images, you can try running jhead on them and it should be able to find the dates in the files. See jhead.
It can then rename the files based on the date for you, then you could separate them by their names/dates.
It may also tell you the GPS latitude/longitude, so you could move them to folders based on their proximity to each other.
Try the -v option to see the full information in a file:
jhead -v recovered123.jpg
Get the time information from the EXIF metadata.
Use this to automatically name and sort the images. Since you likely did not operate two cameras at two different events at the same time, this will work extremely well. Unlesw you managed to destroy this metadata.
I tried to import my data in json format but it took forever to import and I cannot do anything except waiting.
The files consist of a list of images, and for each image, you can find the following fields:
id - the id of the image
band_1, band_2 - the flattened image data. Each band has 75x75 pixel values in the list, so the list has 5625 elements. Note that these values are not the normal non-negative integers in image files since they have physical meanings - these are float numbers with unit being dB. Band 1 and Band 2 are signals characterized by radar backscatter produced from different polarizations at a particular incidence angle.
inc_angle - the incidence angle of which the image was taken. Note that this field has missing data marked as "na", and those images with "na" incidence angles are all in the training data to prevent leakage.
is_iceberg - the target variable, set to 1 if it is an iceberg, and 0 if it is a ship.
Please advise what I can do to try this product on my data. I want to predicted probability that this image is iceberg.
reposting branden murray's solution: you can convert your json to csv.
also here are the currently support file formats for driverless as of version 1.1.6 (May 29 2018)
File formats supported:
Plain text formats of columnar data (.csv, .tsv, .txt)
Compressed archives (.zip, .gz)
Excel files
Feather binary files
Python datatable binary directories
There are 100 image files with different colors .I want to get unique image based on the color
There is no built in Hadoop/Pig API for processing Image data.
To process image data using Pig/MapReduce, use the following steps:
Convert all the images into Sequence File/Files
Key Value
Image_file_id Image Content
Load this file into HDFS.
Use any third party library for detection like "Haar Cascades" as UDF in Pig or call the Java library in MapReduce program.
I want to create a MATLAB code that will create a database of images and when a image is given as input it will search the database and match the given input.After that it will command a microcontroller. I want to know how I'll be able to do the whole thing automatically.The loop will run automatically.
I have created an image, using Platform Builder, for Windows CE6.
As per the legal agreement, I then 'licensed' the NK.BIN image file, again using Platform Builder, using a purchased run-time key that came with 100 licenses.
How can I test that this process has worked?
What is 'different' in the image? Is there a command/action that can be performed to identify a legally stamped CE6 image?
If you are trying to determine if the NK.bin has been built with the correct PID then Stampbin should do the trick:
http://msdn.microsoft.com/en-us/library/ee504718.aspx
Otherwise a search on Viewbin seems to be positive as well:
http://msdn.microsoft.com/en-us/library/ms938075.aspx:
You can use Viewbin.exe tool like "viewbin -t nk.bin" which will give an output comprised of PID[0] - PID[9]. If all these values are 0x00000000 then it means your runtime image is not stamped, otherwise it is stamped.