Spyne.ai
PhotoAiD
FocoClipping
ZapBG
Cutout.Pro
Pixelz
Pixo
autoRetouch
OpenCV
Pandas
Scikit-learn
NumPy
Dataiku
Exploratory
htm.java
Figure Eight
One of the biggest pain points for any online seller is to showcase their products in the best possible manner to grab customer attention and increase conversions.
Spyne is transforming the way businesses create their catalog using state-of-the-art AI technology. No studio. No photography skills. No complex processes. Just Spyne to create stunning catalogs that drive 40% better conversions.
We are building first-of-its-kind AI that would transform the way businesses will create high-impact catalogs without the need for a physical studio.
We are building computer vision and AI technology to automate image processing workflows. This will help any business or marketplace shoot, edit, and publish product visuals at scale, at a fraction of the cost, and time.
We are helping large e-commerce marketplaces in the automotive, food, fashion, real estate, and retail industry create and upgrade high-quality visual catalogs at scale.
Founded in 2018, Spyne is headquartered in Gurugram, India serving 80+ customers across 15+ countries including Amazon India, Flipkart, Karvi, OLACars, Sell Any Car, etc. We are backed by Accel Partners, Storm Ventures, and other marquee investors.
Spyne.ai OpenCVBased on our record, OpenCV seems to be more popular. It has been mentiond 52 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.
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 22 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - 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 / 7 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 7 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
PhotoAiD - Take passport photos where and when you want!
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
FocoClipping - FocoClipping is an online free-to-use image background remover, the key features are as follows : 1. Remove image background 100% automatically. 2. HD output quality up to 3000x 3000 pixels. 3. One click to change backgrounds with new backgrounds.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ZapBG - Remove backgrounds fast & easily with just a few clicks.
NumPy - NumPy is the fundamental package for scientific computing with Python