blackjack-basic-strategy VS process-google-dataset

Compare blackjack-basic-strategy vs process-google-dataset and see what are their differences.

process-google-dataset

Process Google Dataset is a tool to download and process images for neural networks from a Google Image Search using a Chrome extension and a simple Python code. (by masesk)
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blackjack-basic-strategy process-google-dataset
23 1
25 29
- -
2.0 0.0
11 months ago over 2 years ago
JavaScript JavaScript
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

blackjack-basic-strategy

Posts with mentions or reviews of blackjack-basic-strategy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-23.
  • Show HN: Pip install inference, open source computer vision deployment
    4 projects | news.ycombinator.com | 23 Aug 2023
    It’s an easy to use inference server for computer vision models.

    The end result is a Docker container that serves a standardized API as a microservice that your application uses to get predictions from computer vision models (though there is also a native Python interface).

    It’s backed by a bunch of component pieces:

    * a server (so you don’t have to reimplement things like image processing & prediction visualization on every project)

    * standardized APIs for computer vision tasks (so switching out the model weights and architecture can be done independently of your application code)

    * model architecture implementations (which implement the tensor parsing glue between images & predictions) for supervised models that you've fine-tuned to perform custom tasks

    * foundation model implementations (like CLIP & SAM) that tend to chain well with fine-tuned models

    * reusable utils to make adding support for new models easier

    * a model registry (so your code can be independent from your model weights & you don't have to re-build and re-deploy every time you want to iterate on your model weights)

    * data management integrations (so you can collect more images of edge cases to improve your dataset & model the more it sees in the wild)

    * ecosystem (there are tens of thousands of fine-tuned models shared by users that you can use off the shelf via Roboflow Universe[1])

    Additionally, since it's focused specifically on computer vision, it has specific CV-focused features (like direct camera stream input) and makes some different tradeoffs than other more general ML solutions (namely, optimized for small-fast models that run at the edge & need support for running on many different devices like NVIDIA Jetsons and Raspberry Pis in addition to beefy cloud servers).

    [1] https://universe.roboflow.com

  • Open discussion and useful links people trying to do Object Detection
    4 projects | /r/deeplearning | 18 Feb 2023
    * Most of the time I find Roboflow extremely handy, I used it to merge datasets, augmentate, read tutorials and that kind of thing. Basically you just create your dataset with roboflow and focus on other aspects.
  • TensorFlow Datasets (TFDS): a collection of ready-to-use datasets
    3 projects | news.ycombinator.com | 21 Dec 2022
    For computer vision, there are 100k+ open source classification, object detection, and segmentation datasets available on Roboflow Universe: https://universe.roboflow.com
  • Please suggest resources to learn how to work with pre-trained CV models
    2 projects | /r/computervision | 21 Nov 2022
    Solid website and app overall for learning more about computer vision, discovering datasets, and keeping up with advancements in the field: * https://roboflow.com/learn * https://universe.roboflow.com (datasets) | https://blog.roboflow.com/computer-vision-datasets-and-apis/ * https://blog.roboflow.com
  • Suggestion for identification problem with shipping labels?
    3 projects | /r/computervision | 1 Nov 2022
    If you're lacking training images, you can also use [Roboflow Universe](https://universe.roboflow.com) to obtain them (over 100 million labeled images available)
  • Ask HN: Who is hiring? (November 2022)
    20 projects | news.ycombinator.com | 1 Nov 2022
    Roboflow | Multiple Roles | Full-time (Remote) | https://roboflow.com/careers

    Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment.

    Over 100k engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. And we now host the largest collection[2] of open source computer vision datasets and pre-trained models[3].

    We have several openings available, but are primarily looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. (We especially love hiring past and future founders.)

    We're hiring 3 full-stack engineers this quarter and we're also looking for an infrastructure engineer with Elasticsearch experience.

    [1]: https://docs.roboflow.com

    [2]: https://blog.roboflow.com/computer-vision-datasets-and-apis/

    [3]: https://universe.roboflow.com

  • Ask HN: Any good self-hosted image recognition software?
    6 projects | news.ycombinator.com | 22 Sep 2022
  • SAAS for object detection?
    3 projects | /r/computervision | 21 Sep 2022
    Find datasets: https://universe.roboflow.com/
    3 projects | /r/computervision | 21 Sep 2022
    Open source datasets: https://universe.roboflow.com/ Model training: https://docs.roboflow.com/train Model deployment: https://docs.roboflow.com/inference/hosted-api
  • Ask HN: Who is hiring? (September 2022)
    20 projects | news.ycombinator.com | 1 Sep 2022
    Roboflow | Multiple Roles | Full-time (Remote) | https://roboflow.com/careers

    Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment.

    Over 100k engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. And we now host the largest collection[2] of open source computer vision datasets and pre-trained models[3].

    We have several openings available, but are generally looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. (We especially love hiring past and future founders.)

    [1]: https://docs.roboflow.com

    [2]: https://blog.roboflow.com/computer-vision-datasets-and-apis/

    [3]: https://universe.roboflow.com

process-google-dataset

Posts with mentions or reviews of process-google-dataset. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning process-google-dataset yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing blackjack-basic-strategy and process-google-dataset you can also consider the following projects:

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Speed-Coding-Games-in-JavaScript - Games Repository from Speed Coding channel

edenai-javascript - The best AI engines in one API: vision, text, speech, translation, OCR, machine learning, etc. SDK and examples for JavaScript developers.

Tailwind CSS - A utility-first CSS framework for rapid UI development.

notion-auto-pull - Bash script to automatically download a notion workspace

n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.

cost-model - Cross-cloud cost allocation models for Kubernetes workloads [Moved to: https://github.com/kubecost/opencost]

datasets - TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...