284 results about "Pixel color" patented technology

A high-fidelity three-dimensional reconstruction method for a specular reflection plane comprises the steps of decomposing pixel colors into diffuse reflection and specular reflection components based on a 3D Gaussian sphere, introducing a dynamic reflection ratio parameter and a spherical harmonic function coefficient to respectively represent two reflection characteristics, and simulating light multi-reflection behaviors through weight fusion of cumulative projection and a reflection ratio map. Secondly, in combination with monocular inverse depth calibration, depth smoothing constraint of color gradient weighting and edge mutual exclusion loss, geometric consistency is enhanced, and artifacts are suppressed; a progressive multi-resolution training strategy is further adopted, low resolution is gradually optimized to complete resolution, reflection parameters are activated in stages, 3D Gaussian sphere overgrowth and floating artifacts are inhibited, and efficiency and precision are balanced. According to the method, the reconstruction fidelity of the specular reflection scene is remarkably improved while the real-time rendering advantage of the 3DGS is reserved, and the method is suitable for the high-precision modeling fields of virtual reality, augmented reality and the like.

Approaches presented herein provide for the generation of image content including fine objects, such as those that may be less than one pixel in width. Fine objects such as hairs can be represented by curve equations, and curves defined by these equations can be given an inflated width in order to perform conservative hit testing to efficiently identify pixels that a hair might intersect. Once candidate pixels are identified through ray tracing or sampling, for example, false positives or pixels with little hair representation can be removed from consideration. For remaining pixels, a linear representation of the inflated curve can be used to determine intersection points and vertices of a pixel quad corresponding to a hair, which can be used to generate a convex geometric shape representative of the object. The percentage of the pixel area occupied by this geometric shape can be used to determine an alpha or blending value for blending the pixel value of this hair or object with the background pixel color.

A method includes receiving image data captured by a traffic feature detection system. The image data is representative of a traffic feature within an environment. The method includes identifying a type of the traffic feature. The method includes isolating a portion of the image data containing the traffic feature. Based on the portion of the image data containing the traffic feature, the method includes determining a pixel color value for the traffic feature. Based on the type of the traffic feature, the method includes determining an expected pixel color value for the traffic feature. Based on a comparison of the expected pixel color value and the determined pixel color value for the traffic feature, the method includes determining a health status for the traffic feature.

The invention relates to the technical field of remote sensing images, in particular to a method, device and equipment for generating an orthoimage based on point cloud and a storage medium. Comprising the following steps: S1, acquiring point cloud data; s2, carrying out grid processing on the point cloud data; s3, sorting single grid units comprising a plurality of points according to elevation values, retaining top point clouds, determining pixel color values of the grid units, generating a three-channel image with a plurality of pixels, and constructing a preliminary ortho-image map; s4, traversing the three-channel image to identify null value pixel points, extracting coordinate values of a plurality of non-null value pixel points in the neighborhood, and calculating a coordinate azimuth angle difference value; and S5, according to the coordinate azimuth angle difference value, judging whether the null value pixel point is a hole pixel point located in the image, when the hole pixel point exists, carrying out image repairing, and outputting a repaired orthoimage. According to the method, the high-fidelity orthoimage map can be quickly generated, and the processing efficiency is remarkably improved while the authenticity and the integrity of the ground feature color are ensured.

The invention provides a gait identity information desensitization method and system based on sparse contour hopping. The method comprises the steps that S1, a gait video is deframed into an image sequence, and binarization processing is conducted on the image sequence; s2, extracting identity features in the binary image sequence by using a gait recognition model, and calculating an adversarial disturbance matrix of each image according to a loss function; s3, binary image sequence key frames are selected at equal intervals, and adversarial disturbance meeting the pixel jump constraint is added to the human body contour edge in the key frames; s4, embedding the finally added disturbance value into the binary image sequence to obtain a reversible human body contour image sequence; and S5, pixel color backfilling is carried out on the modified binary image sequence, and a desensitized gait video is obtained. According to the method, the loss function of the image sequence before and after desensitization is maximized by means of the gait recognition model, so that the pixel directly generates binary hopping towards the gradient rising direction, non-directional or directional interference on the gait recognition result is realized, and the identity information privacy is protected.

The invention relates to the technical field of image recognition, in particular to a method for recognizing the irrigation state of a plant growth area based on image recognition, which comprises the following steps: acquiring an image of the plant growth area, segmenting the plant area and extracting contour coordinate points of each leaf; and calculating the mean value of the ratios of the centroid spacing to the perimeter of each contour to obtain a leaf contour space distribution factor, and based on the leaf contour space distribution factor and the segmented plant region pixels. According to the method, by extracting the centroid position and the spatial structure feature of the leaf contour, the spatial distribution difference of each leaf in a plant area is quantified, and further through contour coordinate iteration alignment operation, more stable and unified group leaf shape features are obtained, and interference caused by leaf shape difference is reduced; meanwhile, precise quantification and symbiotic relationship analysis of a pixel color channel are adopted, spatial position information and color differences are combined, and a heterogeneity index of fusion of the leaf shape and color distribution is constructed.

The invention discloses a point cloud dyeing method, apparatus and device, and a readable storage medium. The method comprises the steps of obtaining a point cloud frame and a plurality of image frames; aiming at each space point of each camera device, generating an observation transformation matrix used for representing the projection movement condition of the space points on an image plane in the exposure process of the camera devices; generating a relative timestamp for indicating the imaging moment of the spatial point; based on the relative timestamp and the observation transformation matrix, generating a pixel coordinate of the spatial point projected to an image frame of the camera device, and based on the pixel coordinate, performing pixel color picking on the spatial point to obtain a pixel vector; establishing a corresponding relationship between each spatial point of different camera devices and each point cloud in the point cloud frame; and determining a color vector of the corresponding point cloud based on the pixel vector of each spatial point corresponding to the same point cloud. Visibly, according to the method, space-time alignment of the three-dimensional space points and the pixel coordinates on the image frame can be realized by constructing the observation transformation matrix and the relative timestamp, and the point cloud dyeing precision is improved.

The invention belongs to the technical field of display, and particularly relates to a self-adaptive display method of an LCD (liquid crystal display) screen, terminal equipment and a storage medium. And according to the frame rate of the video to be played and the pixel color change condition in the color sequence corresponding to each frame, determining that the duration required for completing each color change in the color sequence by the pixel is within the duration limited by the frame rate, if not, carrying out replacement adjustment on the color in the color sequence by using the replacement color in the replacement color set, and if not, carrying out adjustment on the color in the color sequence by using the replacement color in the replacement color set. According to the method and the device, each color change in the pixel completion color sequence is ensured to be within the limited duration, so that the problem of smear and ghosting during video playing is prevented, and the replacement process is not perceived by a user because the replacement color and the replaced color are the same color which cannot be distinguished for the user, so that the overall watching experience of the user is ensured.

The invention relates to an extraterrestrial celestial body boundary-free scene three-dimensional reconstruction method based on a Gaussian radiation field, and the method comprises the steps: extracting visual features of an input image, and obtaining internal parameters, external parameters and scene sparse point cloud of a camera through feature matching and cluster adjustment; an expanded dense point cloud is calculated according to a light plane intersection mode, a series of three-dimensional Gaussian distributions are constructed, and pixel colors in a given visual angle direction are rendered in a rasterization mode; aiming at a rendering result, guiding a Gaussian position to be accurately close to a scene surface by utilizing pre-estimated depth prior in an optimization process; a scene surface is accurately captured in combination with an explicit and implicit model joint representation mode; and rebuilding a fine and complete three-dimensional mesh model on the surface of the extraterrestrial celestial body by using a marching tetrahedron algorithm according to an optimization result. According to the method, fine three-dimensional reconstruction of the surface of the extraterrestrial celestial body in a boundary-free scene can be realized, the modeling capability of a Gaussian radiation field in the boundary-free scene is enhanced, and the precision and integrity of three-dimensional reconstruction of the surface of the extraterrestrial celestial body are improved.

The invention discloses a space target three-dimensional reconstruction realization method based on radiation field generation. The method comprises the following steps: acquiring image data of a space target for preprocessing; an improved generated radiation field network is built, and an image is sampled to obtain an image patch; obtaining a group of three-dimensional sampling points in a layered sampling mode, performing multi-frequency position coding, splicing with a shape vector, sending into a shape coding layer to obtain feature representation, and inputting into a color head together with a sight direction code and an appearance variable to calculate the color of the sampling points; for each ray, colors of all sampling points are synthesized into a final pixel color based on a volume rendering equation, and the final pixel color is combined into a patch image to be output; inputting the real patch and the patch image into a discriminator, and calculating confrontation loss and discrimination loss; and acting the weight obtained by training on a generator to obtain rotating videos of the space target at different visual angles. The method can realize three-dimensional reconstruction of a space target, and has the advantages of flexible data driving, cross-view geometric consistency, efficient training and the like.

Disclosed in embodiments of the present disclosure are a color value determination method and apparatus, an electronic device, a computer storage medium and a computer program product. The color value determination method comprises: acquiring a shifted color value of each texel amongst a plurality of texels affecting a target pixel, the shifted color value of each texel being obtained by performing first shift processing on a texel color value of the texel on the basis of the texture format of the texel, the numbers of decimal places of decimals of the shifted color values in different texture formats all being the same, and the number of integer digits of said decimals all being the same; on the basis of an impact factor of each texel on the target pixel and the shifted color value of each texel, determining a pixel color value of the target pixel; and according to a restoration mode corresponding to the texture format, restoring the pixel color value so as to obtain a target color value of the target pixel. The present disclosure can reduce the occupied space of hardware modules, thus saving the occupied space for graphics processing units.

The invention relates to the technical field of optical imaging, and discloses a single-pixel color imaging system based on multi-wavelength radio frequency marking. The system comprises a light source module used for generating three laser beams with three optical primary colors; the radio frequency driving module is used for generating a radio frequency complex frequency signal; the light path adjusting module is used for performing heterodyne interference processing on the three laser beams according to the radio frequency complex frequency signal, respectively forming a light spot array and a reference light source and then combining the beams, and generating a combined beam to be incident on a measured target; each laser beam corresponds to one group of sub light spot arrays; sub light spot arrays with aligned spatial positions exist among the three groups of sub light spot arrays; the detected target detection module is used for collecting light data generated after a detected target reflects the combined light beam; and the image inversion module is used for performing image inversion processing on the optical data to generate a true color image of the measured target. According to the system, the light spot array of multi-wavelength laser incidence can be registered in the spatial position.

The invention relates to the field of computer vision, and discloses a laser radar and camera joint calibration method, electronic equipment and a storage medium. The method comprises the following steps: acquiring point cloud data of a plurality of laser radars and image data of a camera; performing motion distortion compensation on the point cloud data to generate a global point cloud map; converting the global point cloud map into a plurality of three-dimensional Gaussian voxels with color attributes and covariance attributes; minimizing the first loss function by jointly optimizing the attribute of the three-dimensional Gaussian voxel and the external parameter of the camera so as to complete the calibration of the external parameter of the camera; wherein the first loss function comprises a color consistency constraint term and a rendering error term, and the color consistency constraint term is used for constraining that observed color attributes of a single three-dimensional Gaussian voxel at multiple moments and multiple visual angles are kept consistent; the rendering error term is a pixel color error between a projection image generated by the three-dimensional Gaussian voxel and image data of the camera. Therefore, the precision of external parameter calibration in a dynamic scene is improved.

The invention discloses a soil color exploration and identification system and method, belongs to the technical field of soil color identification, can effectively reduce the influence of ambient light on soil color discrimination through a standardized color correction board and software image processing, and performs hierarchical division on a soil color identification image along a vertical plane, thereby improving the accuracy of soil color identification. Pixel point color information of a plurality of independent soil layers is obtained, so that the color distribution uniformity of a single layer is judged, then the color distribution condition of the whole image is comprehensively analyzed to divide soil types, and different color recognition modes are selected according to the judged soil types to be compared with a colorimetric card digital image. Compared with a mode of directly extracting color information of an overall image and comparing a colorimetric card, hierarchical division is adopted, single-to-overall soil type judgment is carried out, and a proper recognition mode is selected according to a judgment result, so that the color recognition accuracy is effectively improved.

Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.

The invention discloses a pattern wafer surface three-dimensional morphology reconstruction method, which comprises the following steps of: 1, constructing a small depth-of-field microscopic imaging system, and scanning the surface of a wafer along an optical axis direction to obtain a zoom image sequence; 2, establishing an image sequence space and a color vector space, calculating a pixel color gradient and a dispersion characteristic as a focusing evaluation basis, fitting a Gaussian distribution curve, obtaining a focusing evaluation curve with high steepness and an accurate center position according to a Bayesian prior distribution and posterior distribution principle, and performing focusing evaluation on the focusing evaluation curve; combining the curve peak value with the scanning interval to obtain a wafer surface initial depth map; and 3, performing filtering optimization on the initial depth map, and outputting a final three-dimensional reconstruction result. The method can effectively solve the problem that low-texture and low-contrast area definition evaluation is not accurate in a traditional focusing evaluation method, can improve the focusing peak searching speed and precision, and is suitable for high-precision microscopic three-dimensional reconstruction work of the wafer surface.

The invention provides a power equipment three-dimensional modeling and route planning method based on laser point cloud and image fusion. The method comprises the steps that an original point cloud sequence and an original image sequence collected by an unmanned aerial vehicle and pose information of the unmanned aerial vehicle are acquired; preprocessing the original point cloud sequence to generate a clean point cloud sequence; preprocessing the original image sequence to generate an enhanced image sequence; performing rough matching on the clean point cloud sequence according to the pose information to generate a panoramic scene point cloud; projecting points of the panoramic scene point cloud to the enhanced image sequence; mapping the pixel color to the panoramic scene point cloud by applying an L-M algorithm to generate a color point cloud; inputting the enhanced image sequence into a pre-trained SegFormer semantic segmentation model to obtain semantic probability distribution of each image; mapping the color point cloud to a corresponding image according to the semantic probability distribution to generate a semantic point cloud, the semantic point cloud including color information and semantic information; and generating a three-dimensional scene model according to the semantic point cloud to output an inspection route.

The invention relates to the technical field of video compression, in particular to an AI-based video compression platform, which comprises a key target detection module, an image region division module, a coding level setting module, a parameter adjustment and analysis module and a coding result integration module. According to the method, key region extraction is completed by collecting pixel color combination and contour change information in a video frame image, background and non-background region boundaries are delimited, a region attribute labeling result is constructed, a region distribution classification relation mapping coding level is established, and reference frame and prediction interval configuration is extracted. Real-time adjustment of compression levels is realized by performing normalized combination analysis on textures and motion change trends of different regions, and region fragments under different compression levels are recombined and subjected to unified code stream processing, so that coding resources can be dynamically allocated on the basis of accurately identifying contents in a compression process; the problems of inaccurate target positioning, fixed compression configuration, delayed content response and the like in an existing compression system are effectively solved.

The invention provides a printing image processing method, a thermal printing control method and electronic equipment, and the method comprises the steps: extracting the page information of a to-be-printed document, and converting the to-be-printed document into a bitmap according to the page information; obtaining a global threshold value of each pixel point based on the bitmap; sequentially traversing each pixel in the bitmap, for the traversed target pixel, obtaining a region contrast ratio corresponding to the target pixel, and adjusting a global threshold value according to the region contrast ratio to obtain a local threshold value corresponding to the target pixel; and binarizing the corresponding target pixel according to each local threshold to obtain a binarization result. The local threshold is obtained by adjusting the global threshold through the area contrast, the local threshold can better reflect the pixel color close to the target pixel, the problem that the global threshold cannot effectively distinguish the black pixel from the white pixel in the partial area with the low contrast is solved, accurate binarization operation is performed on the target pixel, and the image quality is improved. The contrast between black pixels and white pixels is improved, and the black and white printing effect is improved.

The invention relates to the technical field of three-dimensional scene reconstruction, and discloses a real-time three-dimensional rendering method and device based on reflection perception and a medium, and the method comprises the steps: recovering a point cloud from an input image, and defining each point as a three-dimensional Gaussian primitive; generating a rendering normal vector diagram and a reflection intensity diagram; extracting a depth map from the input image, and calculating a standard normal vector diagram based on the depth map; generating a mask based on the reflected intensity map to identify a highlight area; calculating the specular reflection color of each pixel based on the rendering normal vector diagram and the ambient light map; performing weighted fusion on the diffuse reflection color and the specular reflection color of each pixel, and outputting a final pixel color; and constructing a joint loss function, performing optimization training on the model by using a gradient descent algorithm, and finally realizing high-quality and real-time three-dimensional scene reconstruction. According to the invention, by introducing a reflection modeling and normal supervision mechanism, the rendering robustness and generalization ability of the system in a complex illumination and reflection environment are effectively improved.

The invention relates to the technical field of computer graphic processing, and discloses a semantic-guided Gaussian point rendering method, system and device and a medium, and the method comprises the steps: obtaining a multi-view image, obtaining a corresponding 2D image feature, carrying out the association with a 3D Gaussian point, and carrying out the distillation of the semantic feature of the 3D Gaussian point; extracting semantic features and position information of each Gaussian point after distillation, generating comprehensive appearance features, and mapping the appearance features to material attributes; performing consistency evaluation between the distorted image and the target diffuse reflection image, and constraining local consistency of a depth map and a normal map of the 3D Gaussian point at the same time, so as to optimize and adjust the 3D Gaussian point through consistency loss; and calculating a final pixel color in combination with the learnable environment map. According to the method, the rendering quality is improved, the material attribute of the object is represented more accurately through the semantic feature distillation and the implicit material dictionary, and the rendering problem of the reflecting surface is effectively solved.

An image highlight removal method and system, a storage medium and a program product relate to the field of general image data processing or production, the method comprising: receiving an input image, converting the input image to a brightness and chrominance separated color space, identifying a highlight pixel region, and generating a highlight mask; expanding outwards by taking the boundary of the highlight mask as a reference, and constructing an annular analysis area; calculating a pixel gradient amplitude and a pixel gradient direction, and generating a linear structure feature data set; calculating a pixel color mean value and a pixel color standard deviation, and generating an abnormal region feature data set; performing defect distribution reasoning based on direction information in the linear structure feature data set and the abnormal region feature data set to generate a structure prior guidance graph; and carrying out source patch constraint according to the structure prior guidance graph, and processing the highlight pixel region to obtain an output image. According to the invention, the highlight removal process can be optimized, and the integrity of equipment defect features in the image is ensured.

In order to better predictively encode pixels of an image block of a video, a method of predicting a block of pixel colors of an image is proposed, comprising: determining a template-based intra mode to derive a prediction applicable to the block; determining a plurality of intra prediction modes, and determining respective costs for the plurality of intra prediction modes; determining that a first TIMD mode is a first intra prediction mode of the plurality of intra prediction modes having the lowest cost of the respective costs, and a second TIMD mode is a second intra prediction mode of the plurality of intra prediction modes having a penultimate cost of the respective costs; determining a third TIMD mode as a non-angular intra prediction mode; performing a verification with respect to the third TIMD mode being different from the first TIMD mode and the third TIMD mode being different from the second TIMD mode; forming a final TIMD mode based on the verification as true, the final TIMD mode comprising a linear combination of the first TIMD mode, the second TIMD mode, and the third TIMD mode; and forming a prediction of the block based on a template of the block and the final TIMD mode.

The approaches presented here enable the generation of image content containing fine objects, such as those less than one pixel wide. Fine objects like hairs can be represented by curve equations, and curves defined by these equations can be exaggerated to perform conservative hit tests and efficiently identify pixels that a hair might intersect. Once candidate pixels are identified, for example, by ray tracing or sampling, false positives or pixels with low hair representation can be eliminated. For the remaining pixels, a linear representation of the exaggerated curve can be used to determine the intersection and vertices of a pixel quadrilateral corresponding to a hair and to generate a convex geometric shape representing the object.The percentage of the pixel area occupied by this geometric shape can be used to determine an alpha or blend value to mix the pixel value of this hair or object with the background pixel color.

The present disclosure relates to an IR Drop compensation method, device, terminal and storage medium. The IR Drop compensation method comprises: determining original channel values of color channels of each pixel in an image frame; wherein the color channels comprise a red channel, a blue channel and a green channel; compensating the original channel values of the corresponding color channels of the corresponding pixels in the image frame according to the original channel values of the color channels of each pixel in the image frame and a luminance attenuation coefficient change curve of the corresponding color channel, so as to realize IR Drop compensation of the image frame, wherein the luminance attenuation coefficient change curve represents a corresponding relationship between a luminance attenuation coefficient of the corresponding color channel and a channel value. In this method, the IR Drop compensation of the image frame is realized by adjusting the channel values of the color channels, which can realize more detailed IR Drop compensation, improve the accuracy of IR Drop compensation, and enrich the applicable scenarios of IR Drop compensation.

This solution belongs to the field of information technology of distribution network, and specifically relates to a distributed edge computing system and method based on the scenario of smart power station. The distributed edge computing method based on the scenario of smart power station includes the following steps: S10: deploying edge computing nodes in each station, collecting sensor monitoring data of each power equipment as first data, collecting each monitoring image data as second data, and sending the first data and the second data to the edge computing node; S20: the edge computing node identifies the preset marked area in the second data, extracts the pixel color information in the marked area as the first information, and compares the first information extracted from the current marked area with the first information extracted from other marked areas. This solution solves the problems of inaccurate leakage monitoring data and low upload speed of the station under the condition of limited operation and maintenance and inspection costs, and at the same time, optimizes the operation and maintenance efficiency.

The application discloses a 4D video generation method fusing monocular vision and terrain elevation data, comprising the following steps: acquiring video frame images and corresponding camera pose data collected by a monocular camera; acquiring terrain elevation data of a target area, and constructing a three-dimensional elevation network model; based on the camera pose data, establishing a ray projection model for pixels in the video frame images, calculating the intersection of the rays and the three-dimensional grid model, and obtaining the reference distance from the monocular camera to the ground surface corresponding to the pixels; generating an initial relative depth map of the video frame images by using a depth estimation model; selecting high-confidence ground pixels from the video frame images as reference points, taking the reference distance corresponding to the reference points as the true value, and performing absolute scale correction on the initial relative depth map to obtain an absolute depth map; performing back projection calculation on the absolute depth map, the camera pose data and pixel color information to generate a three-dimensional point cloud, mapping the three-dimensional point cloud to a real geographic coordinate system, and generating 4D video data in time sequence.

The invention provides an intelligent graph recognition method and device based on collaborative drawing, equipment and a storage medium. The method is applied to the technical field of computers, and comprises the following steps: acquiring a canvas for collaborative drawing, performing pattern recognition processing on a pattern in the canvas for collaborative drawing, determining a boundary of the pattern, and performing segmentation processing on the pattern according to the boundary of the pattern to obtain at least one pattern and a pattern block corresponding to the pattern; the canvas for collaborative drawing is a drawing result obtained by collaborative drawing of a plurality of users; performing intelligent pattern recognition processing on the pattern block, and determining a visual component corresponding to a pattern in the pattern block; pixel point pickup processing is carried out on the graphic block, and each pixel point of the graphic block is traversed to obtain a pixel color value of the graphic block; and the data board is generated according to the visual component corresponding to the graph in the graph block and the pixel color value of the graph block, so that the identification accuracy is improved, and the development efficiency is improved.

The invention discloses a cloud rendering method and device based on a shared cache, equipment and a medium. Receiving a target scene identifier and a target scene view angle pose sent by the target terminal; loading a target scene model file according to the target scene identifier, and converting the target scene model file into a data structure object; loading a target radiance hash table corresponding to the target scene identifier from a public storage server; based on the target scene view angle pose and the target detection light, determining a patch intersection point set having a collision intersection point with patch data in the data structure object; and based on the target radiance hash table, determining a target radiance corresponding to each patch intersection point in the patch intersection point set, calculating a pixel color value of the corresponding patch intersection point in the patch intersection point set according to each target radiance, obtaining a target scene view angle image, and sending the target scene view angle image to a target terminal for display. Therefore, the data calculation amount of cloud rendering is reduced, and the cloud rendering efficiency in a multi-user scene is improved.

A pixel arrangement structure, a display panel, a display apparatus and a mask group are provided. The pixel arrangement structure includes basic pixel units in first and / or second directions. Each basic pixel unit includes five sub-pixels, first to third sub-pixels are of different colors, and third to fifth sub-pixels are of a same color; the first sub-pixel includes opposite first and second sides in the first direction, and opposite third and fourth sides in the second direction; and the second sub-pixel is on and separated from the third side of the first sub-pixel, the third sub-pixel is on and separated from the first side of the first sub-pixel, fourth and fifth sub-pixels are both on the fourth side of the first sub-pixel and are separated from the fourth side of the first sub-pixel, and are separated from each other in the first direction.