dhash | Python library to calculate the difference hash | Hashing library
kandi X-RAY | dhash Summary
kandi X-RAY | dhash Summary
Python library to calculate the difference hash (perceptual hash) for a given image, useful for detecting duplicates
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Top functions reviewed by kandi - BETA
- Hash an image
- Calculate the dhash of an image
- Get grays from image
- Gets the RGB color from an image
- Resample a PIL image
- Force the PIL module to be installed
dhash Key Features
dhash Examples and Code Snippets
Community Discussions
Trending Discussions on dhash
QUESTION
I have a function to create image difference hash and stored in a list in Python:
...ANSWER
Answered 2022-Jan-14 at 13:40Multiprocessing would ideal for this as the hashing is CPU intensive.
Here's what I suggest:
QUESTION
I have an array of elements of the same class, how can I search indexOf with only one element from the class
...ANSWER
Answered 2021-Nov-06 at 22:50The indexOf() method returns the first index at which a given element can be found in the array, or -1 if it is not present. - MDN
You are looking for the element whose value if 0x001003 but listohashs is an array of objects. So you are comparing the object with 0x001003 which won't be equal so it will return -1.
You can use findindex here, You have to find the index of the object whose Dlable property value is 0x001003
QUESTION
I saw this syntax in the python implementation of bitcoin over here.
https://github.com/samrushing/caesure/blob/master/caesure/bitcoin.py
I have never seen this syntax before, can someone explain it to me or show me somewhere in the documentation where I can understand it?
...ANSWER
Answered 2021-Jun-04 at 08:38In Python you can assign functions to variables.
fout.write is a function, so in this example, D is assigned to that function.
D = fout.write
In this line
D ('hash: %s\n' % (hexify (dhash (self.render())),)), you are calling the function D, that is, fout.write. It would be the same as:
fout.write('hash: %s\n' % (hexify (dhash (self.render())),))
QUESTION
I am trying to perform difference hashing with the python ImageHash library and keep getting a numpy error.
The error:
File "/Users/testuser/Desktop/test_folder/test_env/lib/python3.8/site-packages/imagehash.py", line 252, in dhash image = image.convert("L").resize((hash_size + 1, hash_size), Image.ANTIALIAS) AttributeError: 'numpy.ndarray' object has no attribute 'convert'
The code:
...ANSWER
Answered 2021-Apr-27 at 04:42as it is mentioned in imagehash library's document, @image must be a PIL instance.. so you cant set numpy array as input of the dshash function.if you want do some preprocess with opencv, you should convert it into PIL array before setting it into dhash, like this :
QUESTION
I am new to Python and am writing an application to identify matching images. I am using the dHash algorithm to compare the hashes of images. I have seen in a tutorial the following lines of code:
...ANSWER
Answered 2020-Nov-22 at 18:36To break it down, the first line pixel_difference = image_resized[0:, 1:] > image_resized[0:, :-1] is basically doing the following:
QUESTION
Each item in my collection has a 64-bit number, which represents dhash of the image. I want to run a query by this field, which will return all items, that have Hamming Distance more or less than some param.
In MySQL I would use BIT_COUNT function. Is there any built-in analog of it in CosmosDB? If no, then how my HAMMING_DISTANCE UDF should look like since JS doesn't support bitwise operations on 64-bit numbers?
...ANSWER
Answered 2020-Oct-26 at 16:55To solve this I took code from long.js and ImageHash for using in CosmosDB UDF. All cudos to their authors.
See gist it here https://gist.github.com/okolobaxa/55cc08a0d67bc60505bfe3ab4f8bc33c
Usage:
QUESTION
I try to create some hashes on a cuda device and printing them on the host. But at the printf on the host i am getting a read error at position 0x000000000100002F
The relevant lines look like this:
...ANSWER
Answered 2020-Oct-24 at 01:22The memory allocation you are using to hold the hashes is incorrect. To have an array of pointers to the memory for each hash, you would require memory allocated both for the array of pointers, and for the hashes themselves, so something like:
QUESTION
I am not sure at all what changed. There were a couple of app upgrades that I ran which might or might not have caused the issue. I believe this may be an issue with the path but I am really not sure. That is the reason I am posting here. Thanks for your help in advance.
This is what I receive when I attempt to run any NPM command:
...ANSWER
Answered 2020-Sep-09 at 17:59I was able to fix this problem First: I uninstalled Node JS from my machine (I am not sure this was needed but I did it)
Second: I copied all of the directories from the (Node JS install)\node_modules\npm\node_modules directory to the c:\Users(user name)\AppData\Roaming\npm\node_modules\npm\node_modules directory
Now it appears that all the npm stuff works. When I run the two commands to get the current versions it returns the correct information.
D:>node -v
v12.18.3
D:>npm -v
6.14.7
I am not sure how things were confused but it appears that at some point in time over the last couple of years that the AppData location had stopped being updated. When I did an update the path was set back to the AppData and that data was very old. By copying over the node_modules for the new install to the AppData location it appears at this point that everything was updated.
I hope this helps someone else in the future.
QUESTION
I have 2 image folder containing 10k and 35k images. Each image is approximately the size of (2k,2k).
I want to remove the images which are exact duplicates.
The variation in different images are just a change in some pixels.
I have tried DHashing, PHashing, AHashing but as they are lossy image hashing technique so they are giving the same hash for non-duplicate images too.
I also tried writing a code in python, which will just subtract images and the combination in which the resultant array is not zero everywhere gives those image pair to be duplicate of each other.
Buth the time for a single combination is 0.29 seconds and for total 350 million combinations is really huge.
Is there a way to do it in a faster way without flagging non-duplicate images also.
I am open to doing it in any language(C,C++), any approach(distributed computing, multithreading) which can solve my problem accurately.
Apologies if I added some of the irrelevant approaches as I am not from computer science background.
Below is the code I used for python approach -
ANSWER
Answered 2020-Jul-31 at 16:45You should find the answer on how to delete duplicate files (not only images). Then you can use, for example, fdupes or find some alternative SW: https://alternativeto.net/software/fdupes/
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Install dhash
You can use dhash like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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