I have a file in tfrecords format containing images as a dataset. Can anyone suggest a way to get actual images from the tfrecords file.
The above image shows the file properties.
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I have an orto tif image with their annotations in a geojson file, I would like to split this image into several images each image with their corresponding annotations in a separate file .
I will use it afterwards to convert each geojson file into a mask to train my model for construction detection (unet fastai).
I'm using openslide-python to read whole slide images in the Philips format. I am trying to anonymize the data by removing the label associated image by deleting/replacing this:
slide.associated_images["label"]
However it raises:
TypeError: '_AssociatedImageMap' object does not support item assignment
I know this is because Openslide is a reading not writing library, however I can't find a solution to remove the labels for Philips format.
I have RDCL 2015 dataset containing the ground truth and sample images with tiff extension. I want to take in ground truth from the xml files and images from the tiff.
The objective is to read the XML and locate the rows within the .tiff files
I am new to this field so I don't have any idea how it's done any suggestion will be helpful.
Thanks in advance
Does any one have full steps and example for TensorFlow example for passing in your own text files and getting them evaluated against the existing model that comes with examples - using train.py as documented?
Also, if I wanted to train on different input set of say 1000 text files of my own samples, and then use that model for new text files? I know there is documentation but is terse for someone who is not familiar with text classification process.
I was able to run image example against my own images as that was only requiring to swap out one image .jpg file name for myh new image file, but for text it seems to be more involved.
Thanks
Here is an example: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/skflow/text_classification.py
You can set the flag test_with_fake_data to use the fake data in text_train.csv (training samples) and text_test.csv (testing samples) here. Next, you can modify these two files to include whatever data you'd like to have. You will need to do some preprocessing if your existing text files are in a different format.
You need to load the vocabulary file saved during training and process your new text with that. See the eval.py file here
Change the data parameters with your input text and proceed.
I'm working in vc++ 08. I need to read EXIF data of particular JPG file and modify it. In that mostly I need to read Latitude and Longitude data of JPG file and modify it. I searched for library that can give me access to EXIF data of JPG file but after all efforts I ended up here. I don't think there is any header file that can give me access of EXIF data of JPG file in vc++. Please help me out. Any examples will be appreciated. Or referce to any library for read and modify EXIF data of JPG file also appreciated.
Thanks in advance...
Try the Adobe XMP toolkit
It can work with EXIF GPS data - not just XMP and is native C++
Finally got it.
Use exiv2 library. It gives all access to exif data of image file. You can read and modify exif data very easily using this.
And more importantly it is free and open source.
Detailed usage : http://linux.die.net/man/1/exiv2