Abstract: The application relates to a dextran affinity tag and use thereof. The present application provides an affinity tag, which is a segment of dextran binding domain, and can purify a target protein by its affinity with the dextran. The affinity tag of the present application has the advantages of more efficient in preparation and purification, and can be widely used in industrial applications that require protein purification processes.

Abstract: The present disclosure relates to a method, a device and a medium for making up a face. The method for making up the face of the present disclosure includes: obtaining a first face image; determining facial key-points by detecting the first face image; generating a second face image by applying makeup to a face in the first face image based on the facial key-points; determining a first face region by segmenting the first face image, wherein the first face region is a face region that is not shielded in the first face image; and generating a final face makeup image with makeup based on the first face region and the second face image.

Abstract: A method and apparatus for detecting a moving target, an electronic equipment and a storage medium. The method includes obtaining a first frame image and a second frame image which are adjacent, and a rotation matrix and a translation matrix between the first and second frame images, the first and second frame image include the same moving target; extracting first feature points from the first frame image; determining second feature points corresponding to the first feature points from the second frame image based on the second frame image and the first feature points; determining distances between the second feature points and corresponding polar lines based on the rotation matrix and the translation matrix; determining third feature points located on the moving target based on the distances; and detecting the moving target based on the third feature points.

Abstract: The application discloses a method, an apparatus and an electronic device for processing an image. The method includes: acquiring an image with a first rendering style and an image with a second rendering style; generating at least one first intermediate gradient image based on the image with the first rendering style and the image with the second rendering style; wherein the at least one first intermediate gradient image comprises an image in a gradient process from the image with the first rendering style to the image with the second rendering style; and generating a first gradient video based on the image with the first rendering style, the at least one first intermediate gradient image, and the image with the second rendering style.

Abstract: Disclosed are a method, an electronic device, and a storage medium of gesture recognition.

Abstract: A method for detecting a posture, including: acquiring an image to be detected; and inputting the image to be detected into a pre-trained detection model, and detecting a posture category in the image to be detected. The detection model is acquired by training based on a positive sample image and a negative sample image, a basic posture categorization model is acquired by training based on the positive sample image with a marked preset posture category, and the negative sample image is determined based on the basic posture categorization model, and the negative sample image contains no posture of the preset posture category and the positive sample image is an image inputted by an user or an image stored at a preset storage location.

Abstract: The application shows a method, an apparatus, and an electronic device for processing an image. The method includes: obtaining an image of a first rendering style; obtaining an image of a second rendering style according to the image of the first rendering style and a first preset processing model; generating at least one first intermediate gradient image according to the image of the first rendering style, the image of the second rendering style, and a second preset processing model, the at least one first intermediate gradient image comprising an image in a process of gradient from the image of the first rendering style to the image of the second rendering style; generating a first gradient video according to the image of the first rendering style, at least one first intermediate gradient image, and an image of the second rendering style.

Abstract: A method for detecting a posture, including: acquiring an image to be detected; and inputting the image to be detected into a pre-trained detection model, and detecting a posture category in the image to be detected. The detection model is acquired by training based on a positive sample image and a negative sample image, a basic posture categorization model is acquired by training based on the positive sample image with a marked preset posture category, and the negative sample image is determined based on the basic posture categorization model, and the negative sample image contains no posture of the preset posture category and the positive sample image is an image inputted by an user or an image stored at a preset storage location.

Abstract: A driving method suitable for a head mounted device (HMD) is provided. The driving method includes the following operations: moving a first image capture unit and a second image capture unit of the HMD to respectively capture two left-eye images and two right-eye images; calculating a first eye relief according to at least one left-eye feature in the two left-eye images; calculating a second eye relief according to at least one right-eye feature in the two right-eye images; calculating an interpupillary distance (IPD) according to the first eye relief and the second eye relief; and adjusting, according to the IPD, a distance between a first lens and a second lens of the HMD.

Abstract: Embodiments herein disclose methods and systems for generating a 2D-navigation map for collision-free navigation by a plurality of robots. Initially, a 2D-navigation map generator executing at a cloud map server initiates a particle simulation to add a plurality of bubbles to an image of an area. Next, the 2D-navigation map generator executing at the cloud map server, processes the bubble simulation to determine a set of bubbles from the plurality of robots on the image that are overlapping free spaces of the area in the image. Next, the 2D-navigation map generator executing at the cloud map server, generates the 2D-navigation map by connecting the set of bubbles using a plurality of edges, wherein the plurality of edges indicate a navigation path to navigate within the area. Finally, based on the generated 2D-navigation map, the plurality of robots traverses from a current location to another location.

Abstract: The application shows a method, an apparatus, and an electronic device for processing an image. The method includes comprises: obtaining an image of a first rendering style; obtaining an image of a second rendering style according to the image of the first rendering style and a first preset processing model; generating at least one first intermediate gradient image according to the image of the first rendering style, the image of the second rendering style, and a second preset processing model, the at least one first intermediate gradient image comprising an image in a process of gradient from the image of the first rendering style to the image of the second rendering style; generating a first gradient video according to the image of the first rendering style, at least one first intermediate gradient image, and an image of the second rendering style.

Abstract: A method to identify feature points associated with the heart valve movement, heart contraction or cardiac hemodynamics is revealed. The mechanocardiography (MCG) is a technology that makes use of vibrational waveforms acquired using at least one gravity sensor attached on one of the four heart valve auscultation sites on the body surface. The data of the electrocardiography (ECG) is recorded simultaneously with the MCG The feature points are identified by comparing P, R and T points of synchronized ECG with the MCG spectrum. By the time sequences and amplitudes of the feature points, the method provides additional clinical information of cardiac cycle abnormalities for diagnosis.

Abstract: Disclosed are a method, an electronic device, and a storage medium of gesture recognition.

Abstract: A method and apparatus for detecting a moving target, an electronic equipment and a storage medium. The method includes obtaining a first frame image and a second frame image which are adjacent, and a rotation matrix and a translation matrix between the first and second frame images, the first and second frame image include the same moving target; extracting first feature points from the first frame image; determining second feature points corresponding to the first feature points from the second frame image based on the second frame image and the first feature points; determining distances between the second feature points and corresponding polar lines based on the rotation matrix and the translation matrix; determining third feature points located on the moving target based on the distances; and detecting the moving target based on the third feature points.

Abstract: A method for detecting gesture key points can include: acquiring a target image to be detected; determining a gesture category according to the target image, the gesture category being a category of a gesture contained in the target image; determining a target key point detection model corresponding to the gesture category from a plurality of key point detection models; and performing a key point detection on the target image by the target key point detection model.

Abstract: Embodiments of the present invention provide a two-phase process for searching the root causes of the yield loss in the production line 100. In a first phase, process tools and their process tool types that are likely to cause the yield loss are identified, and in a second phase, the process parameters that are likely to cause the yield loss within the process tool types found in the first phase are identified. In each phase, two different algorithms can be used to generate a reliance index (RIk) for gauge the reliance levels of their search results.

Abstract: The disclosure can provide a method for converting an image, an apparatus for converting an image, an electronic device, and a storage medium. The method includes: obtaining an image in RAW format; obtaining a semantic analysis result of the image in RAW format by inputting the image in RAW format into a pre-trained first network model; the first network model being obtained by training based on a labeled training sample corresponding to each of a plurality of first training samples, the first training sample being a sample image in RAW format, and the labeled training sample being a sample image in RAW format obtained by labeling a semantic analysis result on the corresponding first training sample; and determining an image in RGB (Red-Green-Blue) format corresponding to the image in RAW format based on the semantic analysis result of the image in RAW format.

Abstract: A method for detecting key points of skeleton, an apparatus, an electronic device, and a storage medium are provided. The method is implemented as follows. An original image is acquired. The original image includes a plurality of key points of skeleton. Based on a pre-trained stacked hourglass network structure, skeleton key point identification is performed on the original image to obtain heat maps of the plurality of key points. The stacked hourglass network structure includes at least one hourglass network. The at least one hourglass network is configured to perform deep-layer feature learning on feature maps of the plurality of key points based on weight values corresponding to the feature maps.

Abstract: A driving method suitable for a head mounted device (HMD) is provided. The driving method includes the following operations: moving a first image capture unit and a second image capture unit of the HMD to respectively capture two left-eye images and two right-eye images; calculating a first eye relief according to at least one left-eye feature in the two left-eye images; calculating a second eye relief according to at least one right-eye feature in the two right-eye images; calculating an interpupillary distance (IPD) according to the first eye relief and the second eye relief; and adjusting, according to the IPD, a distance between a first lens and a second lens of the HMD.

Abstract: The present disclosure relates to a method, a device and a medium for making up a face. The method for making up the face of the present disclosure includes: obtaining a first face image; determining facial key-points by detecting the first face image; generating a second face image by applying makeup to a face in the first face image based on the facial key-points; determining a first face region by segmenting the first face image, wherein the first face region is a face region that is not shielded in the first face image; and generating a final face makeup image with makeup based on the first face region and the second face image.