We used their DC proxies and Residential proxies. Resi proxies were having quite low success rate. We had to use resi solution from other proxy providers. Unblocker didn't work well either also it was way too expensive.
Based on our record, Bright Data should be more popular than Scikit Image. It has been mentiond 34 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.
Reddit Recap is an application that scrapes subreddits using BrightData and generates concise summaries every two hours. These summaries are then converted into audio briefings, all accessible through a beautiful web app, allowing users to effortlessly stay informed about their favorite communities. - Source: dev.to / 4 months ago
Make sure to sign up on BrightData. Also complete the steps for the initial setup for Proxies & Scraping Infrastructure and Web Scraping API. Please make a note on the WSS Browser Credential, Webscraper Api Token. - Source: dev.to / 4 months ago
So my goal here is creating a web scraper and web searcher using bright and gemini openai compatible model to make cursor composer more smarter with functionality like web search and web scrape. - Source: dev.to / 4 months ago
Paid proxies: services like Bright Data or ScraperAPI provide reliable proxies with better performance and support, but you have to pay. - Source: dev.to / 6 months ago
(Optional) Using a proxy server. You would need to secure proxy services from an external proxy provider (NetNut, BrightData, or similar) to configure things like host, username, and password separately. - Source: dev.to / 6 months ago
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 1 year 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 / over 1 year 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 2 years 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 2 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: about 3 years ago
Oxylabs - A web intelligence collection platform and premium proxy provider, enabling companies of all sizes to utilize the power of big data.
OpenCV - OpenCV is the world's biggest computer vision library
Smartproxy - Smartproxy is perhaps the most user-friendly way to access local data anywhere. It has global coverage with 195 locations, offers more than 55M residential proxies worldwide and a great deal of scraping solutions.
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
NetNut.io - Residential proxy network with 52M+ IPs worldwide. SERP API, Website Unblocker, Professional Datasets.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.