BugHerd VS NumPy
Compare BugHerd VS NumPy and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
featured
BugHerd
Marker.io
Pastel
Usersnap
Userback
Bird Eats Bug
Bugasura
Bugfender
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
BugHerd is the world's leading website feedback and bug-tracking tool. Globally, thousands of leading agencies and marketing teams love it for the ease and collaboration it brings to their website projects.
BugHerd has revolutionised the way agencies collect and manage website feedback from clients and internal teams. It is perfect for teams and individuals involved in website design and development. With BugHerd you can easily pin feedback directly to specific elements of the web pages. It acts as a transparent layer on the website that is visible only to you and your team. Submitted feedback and bugs are sent to a central Kanban task board that provides all stakeholders with full visibility of the project.
Get started in 3 easy steps:
STEP 1
Go to bugherd.com and click Start 14-day Free trial.
STEP 2
Sign up to create your first project. You can test BugHerd out on any website. It will only be visible to you.
STEP 3
And voila! You can start collecting feedback and invite others to try it out with you. It’s that simple.
BugHerdNo features have been listed yet.
Based on our record, NumPy seems to be a lot more popular than BugHerd. While we know about 112 links to NumPy, we've tracked only 4 mentions of BugHerd. 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.
This is a great idea, but scanning through appears to be basically https://bugherd.com/ ? Source: over 1 year ago
Competitors There are a few competitors out there that do something very similar (see https://ruttl.com/, https://usepastel.com/, https://bugherd.com/, https://www.markup.io/). This seems to suggest that there seems to be a general market for such a product. Source: over 1 year ago
Currently using BugHerd for web QA (love it) and looking for something similar for email. Source: over 1 year ago
Bugherd is good for this. Used it extensively when I worked for a web agency and it saved so much time. https://bugherd.com/. - Source: Hacker News / almost 2 years ago
How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 22 days ago
NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 22 days ago
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 28 days ago
This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 30 days ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 months ago
Marker.io - Visual feedback and bug reporting tool for websites
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Pastel - Sticky note-based feedback collection tool for live websites
OpenCV - OpenCV is the world's biggest computer vision library
Usersnap - Usersnap is a customer feedback software for SaaS companies that need to constantly improve and grow their products.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.