The Taobao Pailitao function is a function that many netizens who shop online often use. PolaTao's image search product list interface function means that users can upload a picture of a product, and PolaTao will identify and match it based on the picture to find similar or identical products to the picture, and will search for the product The list is returned to the user. The following is the function introduction of this interface:
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Image upload: Users can upload a product image by calling the API. This can be achieved by uploading the image file directly, or by passing the URL link of the image.
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Image recognition: Polaroid will use image recognition technology to analyze and process the uploaded product pictures to extract the characteristic information of the product.
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Matching search: Based on the extracted product feature information, Pailitao will perform a matching search in the product database to find products that are similar or identical to the uploaded pictures.
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Product list return: After the search is completed, Pailitao will return the matched product list to the user. The list contains information about products that are similar or identical to the uploaded image, such as product name, price, merchant, etc.
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Sorting of results: Pailitao can sort the search results according to the needs of users. For example, sort according to the price level, sales level, evaluation quality and other indicators, so that users can more conveniently choose the most suitable product.
Through Pailitao's image search product list interface, users can easily upload a product picture to search for similar or identical products, and quickly obtain relevant product information and choose to purchase.
item_search_img-Search Taobao products by image (Polaroid)
The code design of Pailitao involves multiple modules and technologies. The following is a basic implementation step and core technology:
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Data access and authorization: Pailitao uses the API provided by Taobao to obtain product information and operation permissions through data access and authorization with Taobao. This can be achieved through authorization mechanisms such as OAuth.
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Image recognition: Pailitao uses image recognition technology to identify product photos taken by users through deep learning algorithms and computer vision technology. Commonly used image recognition algorithms include Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN).
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Product information display: After identifying the product, Pailitao needs to display the relevant product information to the user. This can be achieved through front-end development techniques such as HTML, CSS, and JavaScript. At the same time, data interaction with Taobao API is required to obtain information such as product details.
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Sharing and social networking: Pailitao provides sharing and social networking functions. Users can share identified product information on the platform, and perform operations such as comments, labels, and ratings. This needs to involve back-end development techniques, such as using server-side frameworks (such as Node.js, Java, Python, etc.) and databases to store user information and product data.
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Purchase and rebate: If the user decides to purchase the identified product, Pailitao needs to guide the user to jump to Taobao to complete the purchase process. This can be achieved by generating Taobao promotion links. The rebate function also needs to be connected with Taobao's rebate interface, and realize the tracking and settlement of the rebate amount.
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Data analysis and optimization: Pailitao needs to analyze user operations and feedback data to optimize algorithms and user experience. This can use data analysis and machine learning techniques to process and mine data, such as using tools such as Pandas, NumPy, and Scikit-learn in Python.
It should be noted that the above is only a general implementation step and the core technologies that may be involved. The actual Pailitao code design will be more complicated and detailed. The specific implementation steps and technology selection may be based on specific needs and technology stacks rather different.