OCR Text Recognition is an advanced AI-powered platform that specializes in text recognition and image understanding. It offers a comprehensive solution for extracting text from various sources, including images, screenshots, and PDF files. This versatile tool caters to a wide range of needs in work, study, and daily life, making text extraction and image analysis more accessible and efficient.
Optical Character Recognition
Optical Character Recognition (OCR) tool to recognize the text within an image.
Introduction
Feature
Versatile Input Support
OCR Text Recognition accepts multiple input formats, including:
- Images
- Custom screenshots
- PDF files
This flexibility allows users to extract text from various sources effortlessly.
Free OCR Tools Submission
The platform provides free access to OCR tools, enabling users to:
- Recognize text from images
- Extract text from videos
- Identify text in PDF files
This feature ensures that users can perform text recognition tasks without incurring additional costs.
User-Friendly Interface
OCR Text Recognition boasts a simple and intuitive interface, making it easy for users to:
- Right-click on images to recognize text
- Use "Screenshot Recognition Text" for capturing and analyzing text from web pages
- Navigate through the platform's features effortlessly
Text-to-Image Generation
In addition to text recognition, the platform offers:
- Capability to create images from text
- Integration with GPT-4o for enhanced creative experiences
Extensive OCR Model Library
OCR Text Recognition provides access to:
- Nearly 200,000 OCR models
- Wide variety of applications for work, study, and daily life
- Free usage without subscription requirements
Daily Free Usage
Users can benefit from:
- Daily free uses of the platform
- Exploration of various AI-powered tools
- Support for multiple tasks without additional costs
FAQ
What types of files does OCR Text Recognition support?
OCR Text Recognition supports:
- Images
- Custom screenshots
- PDF files
How do I use OCR Text Recognition on a web page?
To use OCR Text Recognition on a web page:
- Right-click on an image and select "Recognize image text"
- Right-click elsewhere on the page and choose "Screenshot Recognition Text"
How many OCR models are available on the platform?
OCR Text Recognition offers nearly 200,000 OCR models for various applications.
Is a subscription required to use OCR Text Recognition?
No, you can freely use the OCR tools without a subscription. However, if you need more than 20 OCR conversations per day, a subscription may be beneficial.
Does OCR Text Recognition use user information for training data?
No, OCR Text Recognition values user privacy and does not use user data for training purposes. Users can delete their accounts and all associated data at any time.
Can OCR Text Recognition generate images?
Yes, OCR Text Recognition offers text-to-image generation capabilities, allowing users to create images based on text input.
Latest Traffic Insights
Monthly Visits
290.25 M
Bounce Rate
55.49%
Pages Per Visit
2.84
Time on Site(s)
113.64
Global Rank
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Country Rank
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Recent Visits
Traffic Sources
- Social Media:0.68%
- Paid Referrals:0.54%
- Email:0.11%
- Referrals:14.58%
- Search Engines:15.20%
- Direct:68.89%
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)
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.](https://static.right-ai.com/tools/2024/7/3/chromewebstore-google-com-detail-chatgpt-for-google-for-fr-pabeminldebomngnkgffiejipjjaaogi-thumbnail-1720037311.png "Get ChatGPT for Free with Google
You can now access ChatGPT, a powerful language model, for free with Google. Here's how:
Method 1: Google Colab
* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = \"Your input here\"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`
Method 2: Google Apps Script
* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = \"Your input here\"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`
Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.")
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.How to Add ChatGPT to All Google Searches ===================================================== Step 1: Create a Custom Search Engine -------------------------------------- * Go to the [Google Custom Search Engine](https://cse.google.com/) website and sign in with your Google account. * Click on the "New Search Engine" button. * Fill in the required information, such as the name and description of your search engine. * Click on the "Create" button. Step 2: Add ChatGPT to the Search Engine ----------------------------------------- * In the "Setup" tab, click on the "Add" button next to "Sites to search". * Enter the following URL: `https://chat.openai.com/` * Click on the "Add" button. Step 3: Configure the Search Engine -------------------------------------- * In the "Setup" tab, click on the "Edit" button next to "Search engine keywords". * Add the following keywords: `ChatGPT` * Click on the "Save" button. Step 4: Get the Search Engine Code ------------------------------------- * In the "Setup" tab, click on the "Get code" button. * Copy the HTML code provided. Step 5: Add the Search Engine to Your Browser ------------------------------------------------ * Open your browser and go to the "Settings" or "Options" page. * Look for the "Search engine" or "Default search engine" option. * Click on the "Add" or "Manage search engines" button. * Paste the HTML code you copied earlier. * Click on the "Add" or "Save" button. You're Done! =============== Now, whenever you search on Google, ChatGPT will be included in the search results. You can also use the custom search engine URL provided by Google to search directly.
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