Amazon is a prominent e-commerce platform that offers a vast amount of valuable data. This data encompasses various aspects, including product details, pricing information, customer feedback, and emerging trends. Accessing and analyzing this data can be beneficial for sellers monitoring competitors, researchers studying market trends, and consumers making informed purchasing decisions. In this tutorial, we will introduce CapSolver's solution, which can significantly expedite the scraping process.
Consider Using CapSolver to Scrape Amazon
When it comes to scraping large amounts of data from Amazon, manual web scraping can be time-consuming and inefficient, especially as the scale of the task increases. To streamline the process and extract extensive data from Amazon, CapSolver is a recommended solution.
CapSolver offers an efficient and effective way to scrape Amazon by solving CAPTCHAs and automating the data extraction process. With its advanced capabilities, CapSolver can navigate through dynamic sites like Amazon, effortlessly handling JavaScript, AJAX requests, and other complexities that arise during scraping.
Alternatively, if you require structured Amazon data promptly, such as product listings, reviews, or seller profiles, CapSolver provides access to its curated Amazon dataset. This dataset allows you to download and access pre-extracted, high-quality data directly from the CapSolver platform.
By leveraging CapSolver for scraping Amazon, you can significantly enhance the efficiency and accuracy of your data collection efforts. Whether you choose to automate the scraping process or utilize the curated dataset, CapSolver offers a comprehensive solution tailored to your specific needs.
Image-to-text, also known as optical character recognition (OCR), is a technology that converts printed or handwritten text within an image into machine-readable text. It involves using algorithms and computer vision techniques to analyze the visual patterns and structures of characters in an image and translate them into editable and searchable text.
Solving Amazon Imagetotext
:::
Create Task
Create the task with the createTask.
Task Object Structure
Note that this type of task returns the task execution result directly after createTask, rather than getting it
asynchronously through getTaskResult.
Properties | Type | Required | Description |
---|---|---|---|
type | String | Required | ImageToTextTask |
websiteURL | String | Optional | Page source url to improve accuracy |
body | String | Required | base64 encoded content of the image (no newlines) (no data:image/*; base64, content |
module | String | Optional | Specifies the module. Currently, the supported modules are common and queueit |
score | Float | Optional | 0.8 ~ 1 , Identify the matching degree. If the recognition rate is not within the range, no deduction |
case | Boolean | Optional | Case sensitive or not |
Example Request
POST https://api.capsolver.com/createTask
Host: api.capsolver.com
Content-Type: application/json
{
"clientKey": "YOUR_API_KEY",
"task": {
"type": "ImageToTextTask",
"websiteURL": "https://xxxx.com",
// You can choose the module you need to use
// ocr single image model, default common
"module": "queueit",
// base64 encoded image
"body": "/9j/4AAQSkZJRgABA......"
}
}
Example Response
{
"errorId": 0,
"errorCode": "",
"errorDescription": "",
"status": "ready",
"solution": {
"text": "44795sds"
},
"taskId": "2376919c-1863-11ec-a012-94e6f7355a0b"
}