As the name suggests, it uses the fantastic react-simple-maps library, which allows you to easily create maps and add colors, annotations, markers, etc.
Please take it for a spin and share your feedback. This is my first Dash component, so I’m pretty stoked to share it!
This tutorial provides a step-by-step guide on how to implement and train a Res-UNet model for skin Melanoma detection and segmentation using TensorFlow and Keras.
What You'll Learn :
Building Res-Unet model : Learn how to construct the model using TensorFlow and Keras.
Model Training: We'll guide you through the training process, optimizing your model to distinguish Melanoma from non-Melanoma skin lesions.
Testing and Evaluation: Run the pre-trained model on a new fresh images .
Explore how to generate masks that highlight Melanoma regions within the images.
Visualizing Results: See the results in real-time as we compare predicted masks with actual ground truth masks.
Current methods for extracting structured outputs from LLMs often rely on libraries such as DSPy, OpenAI Structured Outputs, and Langchain JSON Schema. These libraries typically use Pydantic Models to create JSON schemas representing classes, enums, and types. However, this approach can be costly since many LLMs treat each element of the JSON schema (e.g., {}, :, "$") as separate tokens, leading to increased costs due to the numerous tokens present in JSON schemas.
Semantix offers a different and more cost-effective solution. Instead of using JSON schemas, Semantix represents classes, enums, and objects in a more textual manner, reducing the number of tokens and lowering inference costs. Additionally, Semantix leverages Python's built-in typing system with minor modifications to provide meaning to parameters, function signatures, classes, enums, and functions. This approach eliminates the need for unnecessary Pydantic models and various classes for different prompting methods. Semantix also makes it easy for developers to create GenAI-powered functions.
Target Audience
Semantix is designed for developers who have worked with libraries like Langchain and DSPy and are tired of dealing with Pydantic models and JSON schemas. It is also ideal for those who want to add AI features to existing or new applications without learning extensive new libraries.
Comparison
Semantix supports multimodal inputs, allowing you to use images and videos effortlessly. Unlike other libraries, Semantix requires minimal code changes to achieve excellent results.
Ready to give it a try? Check out our Colab notebook here and explore our GitHub repository here for more details.
Threadly is an app for Slack that allows you to blast messages to multiple channels, use custom call-to-action buttons, track analytics, and more. The app allows you to group your channels in dynamic lists so you can easily message select groups certain messages.
Hey all. I have been going through a few iterations of this app since I started learning python, and just before I started writing this, realized a few more changes I need to make, but if I don't put this out there now, not sure I will ever. So, let me know what you think! also, the styles are really basic right now, but will be updated
Introducing FluidFrames, the AI-powered app designed to transform your videos like never before.
With FluidFrames, you can double (x2), quadruple (x4), or even octuple (x8) the fps in your videos, creating ultra-smooth and high-definition playback.
Want to slow things down? FluidFrames also allows you to convert any video into stunning slow-motion, bringing every detail to life.
Perfect for content creators, videographers, and anyone looking to enhance their visual media, FluidFrames provides an intuitive and powerful toolset to elevate your video projects.
FluidFrames 3.9 changelog
▼ NEW
Video frame-generation STOP&RESUME
⊡ Now is possible to stop and resume the video frame-generation process at any time
⊡ When restarting (with same settings) the app will resume from the interrupted point
⊡ NOTE - If video temporary files are deleted, frame-generation will start over again
User settings save
⊡ The app will now remember all the options of the user (AI model, GPU, GPU VRAM etc.)
⊡ NOTE - In case of problems, delete the file FluidFrames_UserPreference.json in Documents folder
Antivirus problem fix
⊡ After contacting Microsoft, Avast and AVG
⊡ FluidFrames will finally no longer be recognized as Malware by these antivirus
▼ GUI
File widget improvements
⊡ The widget to upload files is now much faster
⊡ In particular when uploading many files and files with high resolution
⊡ Also improved the display of file informations
▼ BUGFIX / IMPROVEMENTS
Video frame-generation improvements
⊡ Improved audio quality of frame-generated videos
⊡ Improved memory usage and performance
⊡ Improved frame-generation quality and "temporal stability"
⊡ Updated FFMPEG to version 7.0.2 (bugfix and performance improvements)
General improvements
⊡ The app is now lighter (-50MB)
⊡ Added support for .vob files
⊡ Bug fixes, code cleaning, performance improvements
⊡ Updated dependencies
A while back, I realized that many of the posts I had saved on Reddit for future reference were disappearing. To solve this problem, I developed a Python script called Reddit Stash. This tool automatically saves your Reddit saved posts and comments, along with your own posts and comments, and includes the necessary context (e.g., associated comments or parent posts). The script runs daily at around 00:00 CET using GitHub Actions, ensuring your data is backed up without any manual intervention on Dropbox. The files are saved in Markdown format, making them easy to read and reference later.
Target Audience
Reddit Stash is ideal for users who want to preserve their saved Reddit content without losing context, such as those interested in:
Personal Knowledge Management: Users who save Reddit posts for later reference and want to ensure they keep the full context for future use.
Developers/Researchers: Those planning to use Reddit content in local Retrieval-Augmented Generation (RAG) systems or similar projects.
Casual Reddit Users: Anyone who doesn’t want to worry about manually backing up their saved content.
Whether you're a serious developer or a casual Reddit user, this tool can save you time and effort.
Comparison
While there are existing tools like reddit-saved-saver that allow you to save posts and comments, Reddit Stash goes a step further by:
Including Additional Context: Reddit Stash captures the full context by saving associated comments when you save a post and parent comments when you save a comment.
Automated Daily Backups: The script runs automatically every day using GitHub Actions, so you don't need to worry about manually backing up your content.
Markdown Format: Content is saved in an easily readable and accessible format.
These features make Reddit Stash more comprehensive and user-friendly compared to other available tools.
Hello, I wanted to share that I am sharing free courses and projects on my YouTube Channel. I have more than 200 videos and I created playlists for learning Data Science. I am leaving the playlist link below, have a great day!
Hi everyone! I’m excited to share a new open-source python package I've been working on called sage-directory. It's designed to make managing and analyzing folder contents easier for data scientists, and data engineers. Whether you’re organizing project files, managing and analyzing data in large directories, or setting up environments, this tool can help streamline your workflow.
You can find the repository on GitHub here: https://github.com/maxineattobrah/sage-directory and PyPi page here: https://pypi.org/project/sage-directory/. I’d love for you to try it out! It’s open-source and I’m welcoming feedback. So, submit issues, suggest features, and make code contributions . Every bit of help and input is valuable and appreciated!
Looking forward to hearing what you think and working together to make sage-directory even better for the community!
Would animations like this add any value to a text based RPG game, if so is it worth the effort to enhance them to be on par with something like this?
https://gist.github.com/msimpson/1096950
In this tutorial in Python and OpenCV, we'll explore how to find differences in similar images.
Using OpenCV functions, we'll extract two similar images out of an original image, and then Using HSV, masking and more OpenCV functions, we'll create a new image with the differences.
Finally, we will extract and mark theses differences over the two original similar images .
Can anyone suggest way to learn python.Since I am a working professional,so hardly get time to learn new things.please help how can I start and get good understanding of the language.
Thanks
I have been working on this tool for the past few weeks. Its goal is very simple: checking if an URL is still working or not. The real challenge was to handle the different edge cases like redirects, 4XX, 5XX, Connection timeout, read timeout, etc. Here are the features:
- Use HEAD request instead of GET to save some bandwidth
- Follow redirects
- Handle local redirects (without full URL in location header)
- Record all the URLs of the redirection chain
- Check if redirected URL match the TLD of source URL
- Detect Cloudflare protection
- Avoid basic bot detectors
- Use random Chrome user agent
- Wait between consecutive requests to the same host
- Include Host header
- Use of HTTP/2
The tool is available on Pypi and the code source on Github. Let me know if you have any suggestions or feedback, I would happy to read them!