Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 1 year ago.
Improve this question
I need to do Semantic image segmentation based on Unet.
I have to work with Pascal VOC 2012 dataset, however I don't know how to do it, do I manually select images for the train & val and convert them into numpy and then load them into the model? Or is there another way?
If this is the first one I would like to know how to convert all the images present in a folder into .npy.
if i understood correctly, you just need to go through all the files from the folder and add them to the numpy table?
numpyArrays = [yourfunc(file_name) for file_name in listdir(mypath) if isfile(join(mypath, file_name))]
yourfunc is the function you need to write to convert one file from dataset format to numpy table
Related
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 2 years ago.
Improve this question
I am sorry for this type of questions! I searched a lot on google and youtube but i am failed to get the accurate knowledge for extracting an image dataset in a single time.
And after images extraction How should I save it as csv file?
Step by step it will be:
Extract the images Dataset
Save as CSV file
I prefer to extract image Dataset using Keras API module. But I am confused which module will be perfect to use and how should extract? I don't know!
That can be possible with some basic file handling and using libraries.
Check the following link, where images are loaded and saved as pickle files to be used in a neural network. These pickle files can be saved and loaded using a library pickle.
An image is stored as a numpy array which can be converted to csv. Check out the following link for this task.
Closed. This question needs details or clarity. It is not currently accepting answers.
Want to improve this question? Add details and clarify the problem by editing this post.
Closed 2 years ago.
Improve this question
I am extracting multiple dataset into one csv file.
data = Dataset(r'C:/path/2011.daily_rain.nc', 'r')
I successfully assigned one dataset but i still have ten more to work with in the same way. Are there any methods or functions can allow me to assign or combine multiple dataset as one variable?
From what you've described, it sounds like you want to perform the same task on each set of data. If that is the case, then consider using storing your dataset paths in an array, then using a for .. in loop to iterate through each path.
Consider the following sample code:
dataset_paths = [
"C:/path/some_data_file-0.nc",
"C:/path/some_data_file-1.nc",
"C:/path/some_data_file-2.nc",
"C:/path/some_data_file-3.nc",
# ... and the rest of your dataset file paths
]
for path in dataset_paths:
data = Dataset(path, 'r')
# Code that uses the data here
Everything in the for .. in block will be run for each path defined in the dataset_paths array. This will allow you to work with each dataset in the same way.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 4 years ago.
Improve this question
I want to export each dimension (width*height) of hundreds of jpg images to an excel file. So, this excel file will include the name of this image, this image's width, and its height, 3 columns in total. Is there any way I can make it?
Thank you in advance!
The easiest would be with ImageMagick which is included in most Linux distros and is available for macOS and Windows:
magick identify -format "%f,%w,%h\n" *jpg > images.csv
Sample Output
Bean.jpg,656,354
a-0.jpg,800,600
a-1.jpg,800,600
a-2.jpg,800,600
after.jpg,3840,2160
background.jpg,639,454
badge-1.jpg,1200,761
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 7 years ago.
Improve this question
I created a dataset of arrays from PNG images. How can I save this dataset in Python such that I can access it later or in another Python script without having to rescan all the images?
You can use python's pickle library to dump the data to a file.
import pickle
dataset = [1,2,3,4]
with open('my_dataset.pickle', 'wb') as output:
pickle.dump(dataset, output)
then you can load it back in another script.
import pickle
with open('my_dataset.pickle', 'rb') as data:
dataset = pickle.load(data)
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 1 year ago.
Improve this question
How does a site like Google implement a Reverse Image search? Which part of the image are they searching and how do they 'store' the image data?
I know this is a general question, but am trying to implement a basic 'reverse image search' against 100 images that I have to see if the image 'going in' is already there -- or something similar exists.
Hash the input image file and compare with the hashes of the 100 images already present
Check out this blog post:
https://realpython.com/blog/python/fingerprinting-images-for-near-duplicate-detection/