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Source channel @githubtrending · Post #14949 · Jul 12

#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7 YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments. https://github.com/WongKinYiu/yolov7

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djangoproject

@djangoproject · Post #275 · 03/18/2017, 01:51 AM

https://github.com/spotify/luigi Writing batch jobs is generally only one part of processing heaps of data; you also have to string all the jobs together into something resembling a #workflow or a #pipeline. #Luigi, created by Spotify and named for the other plucky plumber made famous by Nintendo, was built to "address all the plumbing typically associated with long-running batch processes." With Luigi, a developer can take several different unrelated data processing tasks — "a Hive query, a Hadoop job in Java, a Spark job in Scala, dumping a table from a database" — and create a workflow that runs them, end to end. The entire description of a job and its dependencies are created as Python modules, not as XML config files or another data format, so it can be integrated into other Python-centric projects. #Machine_learning