nielstenboom / recurring-content-detector Goto Github PK

I used your code to skip intros, had some great success with it.

However I realized that I didn't need to convert the whole video, just a sample of it.

A new argument, sample_percentage, would be great.

In my case I just grabbed the first 10 mins like this:

if framecount > 0:
        stream = ffmpeg.input(input).trim(start=0, end=600)
        if resize_width == 224:

Thanks for a really cool project. I hope and can use this in my own project.

So far I tested CH and CNN (CNN is to slow to be usable and seems to be less precise then CH, can this be related to the fact that i only used 3 episodes?)

Previously i have tried to use opencv phash to extract the credits.
The idea was to check the the hashed frames against the video and if the hash was present in all the episodes of that is most likely a intro, but i never got it working properly because my lack of numpy skills

Not sure how to use this project but I'm always falling into: ValueError: need at least one array to concatenate.
Where does this come from?
I'm using the docker implementation

Currently the parameters are hardcoded in config.py, which is hard to change after you installed the package.

To implement:
Make it so that you can supply these parameters in the main detect() function.

For example

When 10 episodes were present, the script was executed and we get all the timestamp for 10 episodes but when a new episode is downloaded, is it possible to match it against the previous 10 episode without repeating the process for first 10 episodes.

What does s and e mean in your script?? Please use better naming convention

It's not uncommon to have other meta data in with a collection of videos.

If you encounter a file that ffmpeg doesn't like the whole processing loop ends. I'd prefer that it just skips over that file and moves on.

just running the defaults

import recurring_content_detector as rcd rcd.detect("<path/>")

and results with this error

Traceback (most recent call last):
  File "C:\Users\phi\PycharmProjects\pythonProject\main.py", line 2, in <module>
    rcd.detect("Z:\Video\TV Shows\Live Action\Shows\S\Supernatural\Season 6")
  File "C:\Users\phi\AppData\Local\Programs\Python\Python311\Lib\site-packages\recurring_content_detector\__init__.py", line 4, in detect
    return detector.detect(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\phi\AppData\Local\Programs\Python\Python311\Lib\site-packages\recurring_content_detector\detector.py", line 238, in detect
    featurevectors.construct_feature_vectors(   
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\phi\AppData\Local\Programs\Python\Python311\Lib\site-packages\recurring_content_detector\featurevectors.py", line 108, in construct_feature_vectors
    feature_vector = vector_function(img)
                     ^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\phi\AppData\Local\Programs\Python\Python311\Lib\site-packages\recurring_content_detector\featurevectors.py", line 75, in color_hist
    result = get_img_color_hist(img, 100)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\phi\AppData\Local\Programs\Python\Python311\Lib\site-packages\recurring_content_detector\featurevectors.py", line 70, in get_img_color_hist
    main = main / (image.shape[0] * image.shape[1])
                   ^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'shape'

Process finished with exit code 1```

Hi, I want to use this tool, on windows and linux, is it possible to have a package for windows where all the library are working, and same for linux ? I can't install faiss

Your fill_gaps function in detector.py doesn't work as decribed.
For instance :

>>> fill_gaps([0,0,1,0,0,0,0,0,0,1,0,0], 80)
[0,0,1,0,0,0,0,0,0,1,0,0]

Last lookahead rows aren't checked.
I suggest this instead (it looks terrible but does the job) :

def fill_gaps(sequence, lookahead):
    i = 0
    change_needed = False
    look_left = 0
    while i < len(sequence):
        look_left -= 1
        if change_needed and look_left < 1:
            change_needed = False
        if sequence[i]:
            if change_needed:
                for k in to_change:
                    sequence[k] = True
            else:
                change_needed = True
            look_left = lookahead
            to_change = []
        else:
            if change_needed:
                to_change.append(i)
        i+=1
    return sequence

Very nice project by the way, good job.

Your project matches exactly what I have been hoping kodi upnext addon devs would implement. But they feel intro and outro detection is not good enough for them to implement those features. Would it be possible for your app to create edl timing files.

im85288/service.upnext#171

Does the script work with linux ? Thanks