Ludwig Ahgren, a popular streamer and YouTuber, livestreamed his entire life for around a month between March and April 2021.
Every time a Twitch viewer donated, an onscreen timer would increase. If the timer ever decremented so far that it reached zero, the subathon would be over.
Example image(s)
Methodology
image_processing.py
update_bbox finds and updates the bounding box of the timer using a mask to match the background color and Cannny edge detection. This is typically quite fast (< 5 ms), so I call it every frame. This may change in the future.
get_str_from_cropped OCRs that bbox after applying some filters and removing noise.
get_timestamp_from_str is a simple regex that converts a time string (HHH:MM:SS) into a Unix timestamp.
downloader.py
get_frames and process_frame push and pop into a work queue, respectively.
Notes
Samples are 1 / sec. Even if OCR were only 40% successful, this would be more than enough data.
Depending on internet, this may take a while. My initial goal was to spend 1 sec real time per 10 seconds of footage processed. Right now it's about 1:8.
Make OCR more reliable— right now it is only 60-80%. Specifically, the program fails when the timer flashes red or there is too much noise around the timer
In a similar vein, make 240p (or even 144p) usable.
More threads/processes— the program is usually not bound by network IO
Write more tests
Add more data
Write proper docstrings/type hints. Sphinx?
Add SQL DB support
Automatic load balancing—— PID over length of queue?
Known Issues
ETA faulty when start_frac != 0
Threads aren't synchronized— e.g. when frac_done == 0.35, one could be 34% done and another 36%. Smarter frac_done will fix this.
Interrupting with ctrl-C usually causes the csv to delete
React
Typescript
Django
Laravel
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Alibaba
D3
Tencent