micah5/ace-attorney-reddit-bot

👨🏼‍⚖️ reddit bot that turns comment chains into ace attorney scenes

ace-attorney-reddit-bot's Issues

How to use?

This looks interesting, but there aren't any instructions on how to use.

Higher resolution videos

Although I understand that the assets are low-res since they come from a GBA game, the video is rendering at the resolution from said assets which affects the letters and make them (specially names) a bit hard to read.

We should be able to output, at least the letters, at a higher rest than the assets, which may mean probably upscaling.

Generalize it outside of reddit

Being able to take a text/csv format and generate the animation. This is useful to integrate it with many other sites, or even make custom ones.

Ths can be done potentially by using:

characters, comments = load_from_file("file.txt/csv")
characters = anim.get_characters(characters)
anim.comments_to_scene(
    comments, characters, output_filename=output_filename
)

Audio disappears when music file ends

When the court music "03 - Turnabout Courtroom - Trial.mp3" ends, all sounds are then muted.
I think sound should work past that time and music should loop.

Regards

Source for other assets

I was unable to find the asset sources for certain things such as textbox4.png, arrow.png, or objection.gif. Is this also on court records?

I assume assets like helperstand.png can be found on this page.

Much help would be appreciated :)

Use on Linux

First of all, sorry for using GitHub issues for this since it's not what they're for but I truly don't know what to do

My main problem seems to be a lack of codecs of both x264 and mp3. I've already tried to compile from source ffmpeg but it doesn't seem to work because it doesn't find mp3 encoder. I'm on debían

Just opening this issue in case someone struggled with it and has an idea of what to do

Thanks

special character processing

when emojis/special characters are in the processed text, it causes a glitch in the text box that spams the typewriter effect for the duration of the scene. this can be fixed by adding some lines that detect emojis/special characters and removes them.

Typo

Typo in bot_streamable.py at line 498
anim.comments_tob_scene should be changed to comments_to_scene

Include a license

By not including a license with your code (usually in the form of a LICENSE file), people are legally not allowed to fork, contribute or otherwise use the code you've published in their own projects, kinda defeating the point of making it open source.

AssertionError: assets/Sprites-gumshoe/gumshoe-shy.gif does not exist

Or at least is not provided in the pack described in README.md
Thanks.

Suggest to loosen the dependency on textblob

Hi, your project ace-attorney-reddit-bot requires "textblob==0.15.3" in its dependency. After analyzing the source code, we found that the following versions of textblob can also be suitable without affecting your project, i.e., textblob 0.11.1, 0.12.0, 0.13.0, 0.13.1, 0.14.0, 0.15.0, 0.15.1, 0.15.2. Therefore, we suggest to loosen the dependency on textblob from "textblob==0.15.3" to "textblob>=0.11.1,<=0.15.3" to avoid any possible conflict for importing more packages or for downstream projects that may use ace-attorney-reddit-bot.

May I pull a request to further loosen the dependency on textblob?

By the way, could you please tell us whether such dependency analysis may be potentially helpful for maintaining dependencies easier during your development?

---

We also give our detailed analysis as follows for your reference:

Your project ace-attorney-reddit-bot directly uses 3 APIs from package textblob.

textblob.blob.BaseBlob.translate, textblob.blob.BaseBlob.detect_language, textblob.blob.TextBlob.__init__

Beginning from the 3 APIs above, 3 functions are then indirectly called, including 3 textblob's internal APIs and 0 outsider APIs. The specific call graph is listed as follows (neglecting some repeated function occurrences).

[/micah5/ace-attorney-reddit-bot]
+--textblob.blob.BaseBlob.translate
+--textblob.blob.BaseBlob.detect_language
+--textblob.blob.TextBlob.__init__
|      +--textblob.blob.BaseBlob.__init__
|      |      +--textblob.utils.lowerstrip
|      |      |      +--textblob.utils.strip_punc
|      |      +--textblob.blob._initialize_models
|      |      |      +--textblob.blob._validated_param

We scan textblob's versions and observe that during its evolution between any version from [0.11.1, 0.12.0, 0.13.0, 0.13.1, 0.14.0, 0.15.0, 0.15.1, 0.15.2] and 0.15.3, the changing functions (diffs being listed below) have none intersection with any function or API we mentioned above (either directly or indirectly called by this project).

diff: 0.15.3(original) 0.11.1
['textblob.ordereddict.OrderedDict.__ne__', 'textblob.blob.WordList.__str__', 'textblob.classifiers.BaseClassifier.extract_features', 'textblob.classifiers.BaseClassifier', 'textblob.en.sentiments.PatternAnalyzer.analyze', 'textblob.en.taggers.NLTKTagger.tag', 'textblob.ordereddict.OrderedDict.__iter__', 'textblob.blob.WordList.__setitem__', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.BaseBlob.sentiment_assessments', 'textblob.blob.WordList.stem', 'textblob.translate.Translator.detect', 'textblob.translate.Translator.translate', 'textblob._text._read', 'textblob.blob.BaseBlob.ngrams', 'textblob.classifiers.NLTKClassifier.update', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.ordereddict.OrderedDict.__eq__', 'textblob.ordereddict.OrderedDict.__reduce__', 'textblob.blob.WordList.__iter__', 'textblob.base.BaseTagger', 'textblob.en.taggers.NLTKTagger', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.en.taggers.PatternTagger', 'textblob.blob.BaseBlob', 'textblob.en.taggers.PatternTagger.tag', 'textblob.blob.BaseBlob.correct', 'textblob.ordereddict.OrderedDict.__init__', 'textblob.ordereddict.OrderedDict.copy', 'textblob._text.Sentiment.__call__', 'textblob.classifiers.basic_extractor', 'textblob.base.BaseTagger.tag', 'textblob.en.sentiments.PatternAnalyzer', 'textblob.blob.WordList.__init__', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.Word.stem', 'textblob.ordereddict.OrderedDict', 'textblob.blob.WordList.__repr__', 'textblob.classifiers.NLTKClassifier.accuracy', 'textblob.tokenizers.SentenceTokenizer', 'textblob.translate._calculate_tk', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.ordereddict.OrderedDict.__repr__', 'textblob.classifiers.BaseClassifier.__init__', 'textblob._text.Sentiment', 'textblob.classifiers.NLTKClassifier', 'textblob.ordereddict.OrderedDict.__setitem__', 'textblob.blob.WordList.count', 'textblob.ordereddict.OrderedDict.clear', 'textblob.translate._unescape', 'textblob.translate.Translator', 'textblob.ordereddict.OrderedDict.__delitem__', 'textblob.ordereddict.OrderedDict.keys', 'textblob.ordereddict.OrderedDict.popitem', 'textblob.ordereddict.OrderedDict.__reversed__', 'textblob.ordereddict.OrderedDict.fromkeys']

diff: 0.15.3(original) 0.12.0
['textblob.blob.WordList.__str__', 'textblob.classifiers.BaseClassifier.extract_features', 'textblob.classifiers.BaseClassifier', 'textblob.en.sentiments.PatternAnalyzer.analyze', 'textblob.en.taggers.NLTKTagger.tag', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__setitem__', 'textblob.blob.BaseBlob.sentiment_assessments', 'textblob._text._read', 'textblob.classifiers.NLTKClassifier.update', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__iter__', 'textblob.base.BaseTagger', 'textblob.en.taggers.NLTKTagger', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.en.taggers.PatternTagger', 'textblob.blob.BaseBlob', 'textblob.en.taggers.PatternTagger.tag', 'textblob.blob.BaseBlob.correct', 'textblob._text.Sentiment.__call__', 'textblob.classifiers.basic_extractor', 'textblob.base.BaseTagger.tag', 'textblob.en.sentiments.PatternAnalyzer', 'textblob.blob.WordList.__init__', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.classifiers.NLTKClassifier.accuracy', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.classifiers.BaseClassifier.__init__', 'textblob._text.Sentiment', 'textblob.classifiers.NLTKClassifier', 'textblob.blob.WordList.count', 'textblob.translate._unescape']

diff: 0.15.3(original) 0.13.0
['textblob.blob.WordList.__str__', 'textblob.classifiers.BaseClassifier', 'textblob.en.sentiments.PatternAnalyzer.analyze', 'textblob.en.taggers.NLTKTagger.tag', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__setitem__', 'textblob.blob.BaseBlob.sentiment_assessments', 'textblob._text._read', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__iter__', 'textblob.base.BaseTagger', 'textblob.en.taggers.NLTKTagger', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.en.taggers.PatternTagger', 'textblob.blob.BaseBlob', 'textblob.en.taggers.PatternTagger.tag', 'textblob.blob.BaseBlob.correct', 'textblob._text.Sentiment.__call__', 'textblob.classifiers.basic_extractor', 'textblob.base.BaseTagger.tag', 'textblob.en.sentiments.PatternAnalyzer', 'textblob.blob.WordList.__init__', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.classifiers.NLTKClassifier.accuracy', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.classifiers.BaseClassifier.__init__', 'textblob._text.Sentiment', 'textblob.classifiers.NLTKClassifier', 'textblob.blob.WordList.count', 'textblob.translate._unescape']

diff: 0.15.3(original) 0.13.1
['textblob.blob.WordList.__str__', 'textblob.classifiers.BaseClassifier', 'textblob.en.sentiments.PatternAnalyzer.analyze', 'textblob.en.taggers.NLTKTagger.tag', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__setitem__', 'textblob.blob.BaseBlob.sentiment_assessments', 'textblob._text._read', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__iter__', 'textblob.base.BaseTagger', 'textblob.en.taggers.NLTKTagger', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.en.taggers.PatternTagger', 'textblob.blob.BaseBlob', 'textblob.en.taggers.PatternTagger.tag', 'textblob.blob.BaseBlob.correct', 'textblob.blob.WordList.__init__', 'textblob.classifiers.basic_extractor', 'textblob.base.BaseTagger.tag', 'textblob.en.sentiments.PatternAnalyzer', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.classifiers.BaseClassifier.__init__', 'textblob.blob.WordList.count', 'textblob.translate._unescape']

diff: 0.15.3(original) 0.14.0
['textblob.blob.WordList.__str__', 'textblob.classifiers.BaseClassifier', 'textblob.en.sentiments.PatternAnalyzer.analyze', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__setitem__', 'textblob.blob.BaseBlob.sentiment_assessments', 'textblob._text._read', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__iter__', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.blob.BaseBlob', 'textblob.blob.BaseBlob.correct', 'textblob.blob.WordList.__init__', 'textblob.classifiers.basic_extractor', 'textblob.en.sentiments.PatternAnalyzer', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.classifiers.BaseClassifier.__init__', 'textblob.blob.WordList.count', 'textblob.translate._unescape']

diff: 0.15.3(original) 0.15.0
['textblob.blob.WordList.__str__', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__setitem__', 'textblob._text._read', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__iter__', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__', 'textblob.blob.BaseBlob', 'textblob.blob.BaseBlob.correct', 'textblob.blob.WordList.__init__', 'textblob.blob.Word', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.Word.lemmatize', 'textblob.blob.Word.lemma', 'textblob.blob.WordList.count']

diff: 0.15.3(original) 0.15.1
['textblob.blob.BaseBlob', 'textblob.blob.BaseBlob.correct', 'textblob.blob.WordList.__str__', 'textblob.blob.WordList', 'textblob.blob.WordList.append', 'textblob.blob.WordList.__init__', 'textblob.blob.WordList.count', 'textblob.blob.BaseBlob.pos_tags', 'textblob.blob.WordList.__iter__', 'textblob.blob.WordList.__setitem__', 'textblob.blob.WordList.extend', 'textblob.blob.WordList.__repr__', 'textblob.tokenizers.SentenceTokenizer', 'textblob._text._read', 'textblob.blob.WordList.__getitem__', 'textblob.blob.WordList.__getslice__']

diff: 0.15.3(original) 0.15.2
['textblob.blob.BaseBlob', 'textblob.tokenizers.SentenceTokenizer', 'textblob.blob.BaseBlob.correct', 'textblob.blob.BaseBlob.pos_tags']

Therefore, we believe that it is quite safe to loose your dependency on textblob from "textblob==0.15.3" to "textblob>=0.11.1,<=0.15.3". This will improve the applicability of ace-attorney-reddit-bot and reduce the possibility of any further dependency conflict with other projects.

Crash if 15 or more authors

It'll crash if there are more than 15 authors in the scene.
I tried to solve it using this code

available_characters = list(
                filter(
                    lambda character: character not in characters, rnd_characters
                )
            )
            if (len(available_characters) == 0):
                available_characters = rnd_characters
            rnd_character = random.choice(available_characters)

But it crash at a later point due to how the code works
Thanks