StandupBot is an easy to use bot that automates your team’s standups, check-ins or any kind of recurring status update meetings, without breaking the bank. Trusted by thousands of teams to run over a million standups in our 8+ year history.
Unlike other tools that try to do way too things and are super confusing to manage, we focus on what you really need to automate your team’s meetings:
⚡️Fast setup: From install to first meeting in under 60 seconds. Great defaults to get you going and super easy to change to your needs.
👥 Multiple teams and projects: Create as many standups or status meetings you need for different projects or teams.
🕘 100% asynchronous: Everyone participates when it’s more convenient for them.
📃 Standup Report: Receive an easy-to-read report via email and Slack when the meeting is done.
👀 “Just following” mode: Select who's actively participating in meetings and who's only following through reports.
📆 Flexible scheduling: Schedule your meetings at the days and times you need. Automatically excuse people from meetings when they’re on vacation.
✅ Participation reports: Team- and individual-level participation reports, so you can easily see who needs some encouragement to share their updates more frequently.
🔔 Automatic reminders: We’ll be the friendly drill-sergeant for your team reminding everyone that hasn’t submitted their standup to do so before the meeting window closes.
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Based on our record, Scikit Image seems to be more popular. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics. - Source: dev.to / about 2 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 6 months ago
This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/. Source: over 1 year ago
Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/. Source: over 1 year ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 2 years ago
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