Best AI tools for< Stain Remover >

Remove Handwriting is a free online tool that uses artificial intelligence to remove handwriting from images and PDFs. It can handle a variety of complex document image issues, including curling, shadows, wrinkles, stains, finger obstructions, text showing through from the back, and moiré patterns. It can also detect the overall shape of documents, accurately locate areas, and intelligently correct various distortions caused by warping and creasing. Remove Handwriting is easy to use. Simply upload an image or PDF, and the AI will automatically remove the handwriting. Within a few seconds, you will receive an image or PDF without any handwriting.

ONVY is an AI Health Coach application designed for business professionals and athletes to optimize health and performance. It offers personalized insights and actionable feedback by analyzing data from fitness trackers. Users can manage recovery, sleep, activity, and mental fitness, aiming to achieve peak performance in sports, career, and life. The app merges the latest health and performance science with AI technology to provide users with clear steps to enhance their overall well-being.

All in One Accessibility™ is an AI-based accessibility solution for quick website accessibility compliance. It enhances accessibility for WCAG 2.0, 2.1 and 2.2, ADA, Section 508, California Unruh, Australian DDA, European EAA EN 301 549, UK Equality Act (EA), Israeli Standard 5568, Ontario AODA, Canada ACA, Australian DDA, Brazilian Inclusion Law (LBI 13.146/2015), German BITV, France RGAA, Spain UNE 139803:2012, Italian Stanca Act, Switzerland DDA, and Austrian Web Accessibility Act (WZG) standards.

SubstrateAI is an artificial intelligence company that creates, acquires, and scales businesses in various sectors such as Health, Finance, Human Resources, and Energy. They develop products and services based on proprietary technology and are listed on stock exchanges in Spain, the UK, and the US. SubstrateAI collaborates with Subgen AI, a subsidiary providing AI solutions to companies and governments globally. The company's technology is inspired by biology and continuously evolves through the daily efforts of researchers.

The Visualizer is an AI-powered tool designed to map out and summarize various types of content such as papers, YouTube videos, documents, podcasts, websites, lectures, articles, and PDFs. It helps users cut down reading time and absorb knowledge faster by providing visual summaries. The tool is trusted by over 3000 educators and learners and is known for its superb performance on different devices. The Visualizer uses AI-generated mind maps to simplify complex topics into visual formats, making it easier to understand and remember detailed concepts. It also reduces mental strain, allowing users to focus better on creative solutions and everyday problem-solving.

ShellChatGPT is a shell wrapper for OpenAI's ChatGPT, DALL-E, Whisper, and TTS, featuring integration with LocalAI, Ollama, Gemini, Mistral, Groq, and GitHub Models. It provides text and chat completions, vision, reasoning, and audio models, voice-in and voice-out chatting mode, text editor interface, markdown rendering support, session management, instruction prompt manager, integration with various service providers, command line completion, file picker dialogs, color scheme personalization, stdin and text file input support, and compatibility with Linux, FreeBSD, MacOS, and Termux for a responsive experience.

This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=