公开(公告)号：GB2625694B

公开(公告)日：2025-02-05

申请号：GB202405432

申请日：2022-10-26

Applicant: SHOPIFY INC

Inventor： PENG YU

IPC: G06T5/00 ,  G06T3/40 ,  G06T5/10 ,  G06T9/00 ,  H04N1/387

Abstract: A computer-implemented method and system for generating a blurred image from an original image. The method and system generate the blurred image using a process that enables fast efficient decoding of the compact encoded blurred image by a client device. The method may include transforming an original image to a block of coefficients in a frequency domain, low-pass filtering the block of coefficients in the frequency domain to produce a block of filtered coefficients, inverse transforming the block of filtered coefficients to produce a blurred image in a pixel domain, encoding the blurred image using a lossy-compression image encoder to produce an encoded blurred image, and transmitting the encoded blurred image to a client device for reconstruction and display by the client device.

公开(公告)号：GB2625694A

公开(公告)日：2024-06-26

申请号：GB202405432

申请日：2022-10-26

Applicant: SHOPIFY INC

Inventor： PENG YU

IPC: G06T5/00 ,  G06T3/40 ,  G06T5/10 ,  G06T9/00 ,  H04N1/387

Abstract: A computer-implemented method and system for generating a blurred image from an original image. The method and system generate the blurred image using a process that enables fast efficient decoding of the compact encoded blurred image by a client device. The method may include transforming an original image to a block of coefficients in a frequency domain, low-pass filtering the block of coefficients in the frequency domain to produce a block of filtered coefficients, inverse transforming the block of filtered coefficients to produce a blurred image in a pixel domain, encoding the blurred image using a lossy-compression image encoder to produce an encoded blurred image, and transmitting the encoded blurred image to a client device for reconstruction and display by the client device.

公开(公告)号：US20240046197A1

公开(公告)日：2024-02-08

申请号：US18489912

申请日：2023-10-19

Applicant: SHOPIFY INC.

Inventor： GEORGE YACOUB ,  PENG YU ,  ALI KIYAN AZARBAR ,  VAHE KHACHIKYAN ,  SIAVASH GHORBANI

IPC: G06Q10/0833 ,  G06Q10/0835 ,  G06Q10/083

CPC classification number: G06Q10/0833 ,  G06Q10/0835 ,  G06Q10/0838

Abstract: When a merchant ships a product to a buyer, the merchant may wish to push shipping status updates to the buyer. Moreover, the buyer may wish to receive a notification when a shipping event has occurred in order to remain informed regarding the shipping status of their package without actively checking the package's status with the carrier. In some embodiments, there is provided a computer-implemented system and method that obtains a tracking identifier for a package, transmits the tracking identifier to a carrier's computing interface (e.g. the carrier's API), receives back an indication of the most recent shipping event, predicts the time of a next shipping event at least based on the most recent shipping event, and retransmits the tracking identifier to the computing interface based on the predicted time of the next shipping event.

公开(公告)号：US20230196741A1

公开(公告)日：2023-06-22

申请号：US17554474

申请日：2021-12-17

Applicant: SHOPIFY INC.

Inventor： KSHETRAJNA RAGHAVAN ,  KYLE BRUCE TATE ,  PENG YU ,  NIKLAS ITÄNEN ,  XIAOXIAO LI

IPC: G06V10/774 ,  G06V10/776 ,  G06V10/762

CPC classification number: G06V10/7747 ,  G06V10/776 ,  G06V10/7635

Abstract: A data partitioning system receives an input dataset for e-commerce products, each sample containing attributes and associated values for each product including at least an image; represents each sample as a node on a graph to provide a graph of nodes for the dataset; measures a relative similarity distance between each pair of nodes based on comparing at least image values for the attributes; determines for each pair of nodes whether they are related if the similarity distance between them is below a defined threshold, and if related, generate an edge between them on the graph; group the connected nodes into a first or a second group such that the grouped nodes have no edges connecting them to nodes in the other group and have a shortest relative similarity distance with each other. The groups are used as training dataset and testing data sets for a supervised machine learning classifier.