CN111382747A - Data marking method, computer device and computer readable storage medium - Google Patents
Data marking method, computer device and computer readable storage medium Download PDFInfo
- Publication number
- CN111382747A CN111382747A CN201811652805.9A CN201811652805A CN111382747A CN 111382747 A CN111382747 A CN 111382747A CN 201811652805 A CN201811652805 A CN 201811652805A CN 111382747 A CN111382747 A CN 111382747A
- Authority
- CN
- China
- Prior art keywords
- marking method
- category
- clothes
- data marking
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/20—Scenes; Scene-specific elements in augmented reality scenes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Image Analysis (AREA)
Abstract
The embodiment of the invention discloses a data marking method, a computer device and a computer readable storage medium, wherein the data marking method comprises the following steps: cutting a video containing at least one character and clothes thereof to obtain a plurality of pictures containing the character and the clothes thereof; leading a plurality of pictures containing characters and clothes thereof into a labeling tool; and framing the clothing objects in each picture by using the labeling tool, and labeling the framed clothing objects according to the main category, the sub-category and the specific category. The marking method for video tracking is specially designed by training the algorithm to better utilize the clothing attribute of the person, the gender characteristic of the person and even the accessory attribute of the person in the video for identification, so that the algorithm can effectively improve the accuracy of the algorithm with less training data sets, and further the algorithm can be deeply analyzed and applied based on the clothing, the accessory and other information of the person in the video.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a data marking method, a computer device, and a computer-readable storage medium.
Background
The explosive growth of artificial intelligence leads to great demand for data, and a new industry-data service is also promoted. Video analysis is an important application direction of artificial intelligence, data is closely related to the quality of a video analysis product, and the artificial intelligence is considered to have three major elements, namely calculation power, an algorithm and data, by the consensus formed in the industry. At present, most of data services in the field of video analysis are data labels aiming at simple object identification or data labels aiming at human behavior prediction in videos, and data labels applied to video analysis are not deeply expanded or explored.
However, the prior art does not utilize video recognition to identify the apparel attributes of the person, the gender characteristics of the person, or even the accessory attributes of the person.
Disclosure of Invention
In order to solve the above technical problem, a first aspect of an embodiment of the present invention provides a data marking method, where the data marking method includes:
cutting a video containing at least one character and clothes thereof to obtain a plurality of pictures containing the character and the clothes thereof;
leading a plurality of pictures containing characters and clothes thereof into a labeling tool;
and framing the clothing objects in each picture by using the labeling tool, and labeling the framed clothing objects according to the main category, the sub-category and the specific category.
Further, the data marking method further comprises the following steps:
and marking the gender of the figure corresponding to the clothing object in each picture by using the labeling tool.
Further, the data marking method further comprises the following steps:
and marking identification codes on the figures corresponding to the clothing objects in each picture by using the labeling tool.
Further, the data marking method further comprises the following steps:
and converting the pictures corresponding to the clothing objects labeled according to the main category, the sub-category and the specific category into json or xml format files.
Further, in the above data marking method, the labeling tool is a label img tool.
Further, in the above data marking method, the step of cutting the video containing at least one person and clothing thereof to obtain a plurality of pictures containing the person and clothing thereof includes:
cutting a video containing at least one character, clothes and accessories thereof to obtain a plurality of pictures containing the character, the clothes and the accessories thereof;
the step of guiding a plurality of pictures containing characters and clothes thereof into the labeling tool comprises the following steps:
leading a plurality of pictures containing characters, clothes and accessories thereof into a labeling tool;
the data marking method further comprises:
and utilizing a labeling tool to frame the accessory objects in each picture, and labeling the framed accessory objects according to the main category, the sub-category and the specific category.
Further, in the above data marking method, the main category of the apparel includes: upper outer garment, lower outer garment, footwear, headwear;
the subcategories of the jacket comprise a jacket, a shirt, a T-shirt, a vest and a suit, and the specific categories of the suit comprise a dovetail, a single-button suit, a double-button suit and a three-button suit; or
The sub-categories of the head wear category comprise a hat, a headband and glasses, and the specific categories of the glasses comprise presbyopic glasses, sunglasses and myopia glasses.
Further, in the above data marking method, the main categories of the accessories include: upper garment accessories, lower garment accessories and hand accessories;
subcategories of the jacket accessory include a tie, a shawl, and a scarf; the specific types of the tie comprise a round tie, a triangular tie and a bow tie;
or the subcategories of the lower clothes accessories comprise belts and socks; specific classes of belts include cowhide belts, crocodile belts.
A second aspect of embodiments of the present invention provides a computer apparatus comprising a processor for implementing the steps of the data marking method described above when executing a computer program stored in a memory.
A third aspect of the embodiments of the present invention provides a computer-readable storage medium having a computer program stored thereon; the computer program realizes the steps of the data marking method described above when being executed by a processor.
The embodiment of the invention provides the data marking method, the computer device and the computer readable storage medium, the data marking method aims to better utilize the clothing attribute of the person, the sex characteristic of the person and even the accessory attribute of the person in the video identification through a training algorithm, and a video tracking marking method is specially designed, so that the algorithm can effectively improve the accuracy of the algorithm with less training data sets, and further the algorithm can be deeply analyzed and applied based on the clothing, the accessory and other information of the person in the video.
Drawings
FIG. 1 is a flow chart of a method of marking data according to one embodiment of the present invention.
Fig. 2 is a flow chart of a method of data marking according to another embodiment of the present invention.
Detailed Description
The marking method for video tracking is specially designed by training the algorithm to better utilize the clothing attribute of the person, the gender characteristic of the person and even the accessory attribute of the person in the video for identification, so that the algorithm can effectively improve the accuracy of the algorithm with less training data sets, and further the algorithm can be deeply analyzed and applied based on the clothing, the accessory and other information of the person in the video. To explain technical contents, structural features, and objects and effects of the technical solutions in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
FIG. 1 is a flow diagram of a data marking method 100 according to one embodiment of the invention. The data marking method 100 includes steps 102, 104, and 106.
Step 102: and cutting the video containing at least one character and the clothes thereof to obtain a plurality of pictures containing the character and the clothes thereof.
Step 104: and leading a plurality of pictures containing the characters and the clothes thereof into a labeling tool. In the embodiment of the invention, the labeling tool is a LabelImg tool.
Step 106: and framing the clothing objects in each picture by using the labeling tool, and labeling the framed clothing objects according to the main category, the sub-category and the specific category.
Further, in an embodiment of the present invention, the data marking method 100 further includes: and converting the pictures corresponding to the clothing objects labeled according to the main category, the sub-category and the specific category into json or xml format files.
In one non-limiting embodiment of the present invention, the main categories of apparel include: upper outer garment, lower outer garment, footwear, headwear.
The sub-categories of the jacket comprise a jacket, a shirt, a T-shirt, a vest and a suit, and the specific categories of the suit comprise a dovetail, a single-button suit, a double-button suit and a three-button suit. Or the sub-categories of the head wear category comprise a hat, a headband and glasses, and the specific categories of the glasses comprise presbyopic glasses, sunglasses and myopia glasses.
Further, in an embodiment of the present invention, the data marking method 100 further includes: and marking the gender of the figure corresponding to the clothing object in each picture by using the labeling tool.
Further, in an embodiment of the present invention, the data marking method 100 further includes: and marking identification codes on the figures corresponding to the clothing objects in each picture by using the labeling tool.
Fig. 2 is a flow chart of a data marking method 200 according to another embodiment of the present invention. Data marking method 200 includes steps 202, 204, 206, and 208.
Step 202: and cutting the video containing at least one character and the clothes and accessories thereof to obtain a plurality of pictures containing the character and the clothes and accessories thereof.
Step 204: and leading a plurality of pictures containing the characters, the clothes and the accessories thereof into a labeling tool. In the embodiment of the invention, the labeling tool is a LabelImg tool.
Step 206: and framing the clothing objects in each picture by using the labeling tool, and labeling the framed clothing objects according to the main category, the sub-category and the specific category.
Step 208: and utilizing a labeling tool to frame the accessory objects in each picture, and labeling the framed accessory objects according to the main category, the sub-category and the specific category.
Further, in an embodiment of the present invention, the data marking method 100 further includes: and converting the pictures corresponding to the clothing objects and the accessory objects which are labeled according to the main category, the sub-category and the specific category into json or xml format files.
In one non-limiting embodiment of the invention, the main categories of accessories include: upper garment accessories, lower garment accessories and hand accessories.
Subcategories of the jacket accessory include a tie, a shawl, and a scarf; the specific types of the tie comprise a round tie, a triangular tie and a bow tie; or the subcategories of the lower clothes accessories comprise belts and socks; specific classes of belts include cowhide belts, crocodile belts.
Further, in an embodiment of the present invention, the data marking method 200 further includes: and marking the sex of the figures corresponding to the clothing object and the accessory object in each picture by using the labeling tool.
Further, in an embodiment of the present invention, the data marking method 100 further includes: and marking identification codes on the figures corresponding to the clothing objects and the accessory objects in each picture by using the labeling tool.
The invention designs a set of data labeling method based on video tracking, which can efficiently produce data with high quality level on one hand, and can greatly improve the accuracy and effectiveness of the algorithm by using fewer data sets on the other hand, thereby efficiently and accurately identifying the gender, clothes, accessories and the like of people in the video.
The data marking method of the present invention is described below by referring to a specific example, and a marking method for video tracking includes the following steps: step 1: a marking tool was developed. Step 2: the method comprises the steps of collecting video data, carrying out image cutting processing on the video, and carrying out data cleaning on the collected video and subsequent picture data at the same time, so as to ensure that the quality of the data meets requirements. And step 3: and (4) carrying out picture marking on the picture data cleaned in the step (2). And 4, step 4: and (5) quality inspection of the marked data is carried out, and the quality of the marked data is ensured.
The method comprises the following specific steps:
the tool development involves two steps of secondary development based on LabelImg and construction of a marking working environment, a function capable of generating json format files needs to be developed based on the LabelImg secondary development, and the marking working environment is constructed in an environment where series software needs to be installed to support the secondary development function.
The data cleaning comprises four steps of video acquisition, video quality inspection, video image cutting and image quality inspection, wherein the video is converted into the image according to a certain rule in one step, and two quality inspection links are designed in the process to ensure that the data is sufficiently cleaned.
The data labeling is mainly to label the pictures produced in the previous steps, wherein one of the labeled key points is the range of object selection frame selection, and the other key point is the classification rule of the object.
The data inspection stage is the last link, and a set of quality inspection rules are designed to ensure the quality of the labeled data.
The implementation method of the data marking of the invention comprises the following steps:
(1) tool development
Based on LabelImg secondary development: the current LabelImg has limited functions, and considering that a json-format file is a text format completely independent of a programming language to store and represent data, is easy to read and write by people, is easy to analyze and generate by a machine, and effectively improves the network transmission efficiency, so that the function of automatically generating the json-format file is developed based on LabelImg software, and jpg pictures labeled by the LabelImg are automatically converted into the json format, so that key elements of data labeling, such as coordinate information of object framing, attribute information of objects, number information of the objects and the like, can be reserved.
Marking tool environment construction: in order to support the function of automatically generating json format files, corresponding environments need to be built, specifically, software packages to be installed are open-source and are respectively a python running environment, pyQT, pip and lxml, and in the process of installing the 4 pieces of software, environment variables of a windows system need to be set so that all the software packages can run normally.
(2) Data cleansing
The video acquisition has specific requirements, firstly, the number of people in the video is between 1 and 4, the length of the video is between 30 and 60 seconds, and the video has definition of more than 720 p; secondly, the content of the video is mainly used for displaying the dress of the current person, and special shooting skills or special effect processing are not needed in the video.
The video quality inspection is mainly to design a link in the process of strictly eliminating video which does not meet the requirements.
The video cutting function is to cut the video into independent pictures, the corresponding cutting requirement is to sample video clips at a frame rate of 8 frames per second, and the pictures after cutting are required to be clearly visible.
Similarly, a picture quality inspection link is also designed so as to eliminate the picture which does not meet the requirement.
(3) Data annotation
After the above steps, the picture data is imported into the LabelImg software which is developed secondarily for frame selection and labeling. Meanwhile, in the labeling process, data classification needs to be carried out on the labeled objects. And the corresponding labeling rule and classification rule are provided. The labeling rules require explicit coordinate information for the selected objects, labeling of more than or equal to 70% of the objects displayed in the picture (whereas less than 30% of the objects are not labeled), and a unique ID for each object (if the corresponding object appears in the subsequent picture, the ID is kept constant). The classification rules require that the apparel is classified according to the level logic, namely, the apparel is sequentially subdivided according to the categories of main categories, sub-categories and specific categories, for example, a coat or jacket belongs to the specific categories, the sub-category of the upper layer is the coat, and the main category of the upper layer is the coat; the accessory is also subdivided by the classification logic; in addition, it is also required that the human beings are classified into two categories, namely, male and female. In the specific classification, the object is named, and the naming rule is a classification rule, for example, a records _ sockets _01, wherein the records _ sockets "represents the clothing attribute of the object, and the" 01 "represents the ID of the object. Although the classification rules are described in, for example, Chinese, in practice, all classifications must be English names.
(4) Data inspection
The data quality is one of the cores of data labeling, and only high-quality data can train a high-quality algorithm. In quality inspection, conditions such as label missing, label error, unclear classification, classification error and the like need to be strictly examined, a corresponding quality inspection detection report needs to be issued, a picture with quality problems needs to be returned to the previous link, and the quality inspection link can be entered again after the picture is corrected again according to the quality inspection report.
In summary, by adopting the data marking method proposed by the embodiment of the invention, the clothing objects of the characters in the video, including accessories, such as bags, necklaces, bracelets and other objects, can be clearly marked one by one, and meanwhile, the key information of the data can be retained in less storage space, so that the algorithm can be favorably used for learning corresponding elements or objects in the video in a targeted manner, and the effectiveness and intelligence of the algorithm are improved.
An embodiment of the present invention further provides a computer apparatus, which includes a processor, and the processor is configured to implement the steps of the data marking method described above when executing a computer program stored in a memory.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the data marking method described above are implemented.
Those skilled in the art will appreciate that the above embodiments are merely exemplary embodiments and that various changes, substitutions, and alterations can be made without departing from the spirit and scope of the invention.
Claims (10)
1. A data marking method, characterized in that the data marking method comprises:
cutting a video containing at least one character and clothes thereof to obtain a plurality of pictures containing the character and the clothes thereof;
leading a plurality of pictures containing characters and clothes thereof into a labeling tool;
and framing the clothing objects in each picture by using the labeling tool, and labeling the framed clothing objects according to the main category, the sub-category and the specific category.
2. The data marking method as claimed in claim 1, further comprising:
and marking the gender of the figure corresponding to the clothing object in each picture by using the labeling tool.
3. The data marking method as claimed in claim 1, further comprising:
and marking identification codes on the figures corresponding to the clothing objects in each picture by using the labeling tool.
4. The data marking method as claimed in claim 1, further comprising:
and converting the pictures corresponding to the clothing objects labeled according to the main category, the sub-category and the specific category into json or xml format files.
5. The data marking method as claimed in claim 1, wherein: the labeling tool is a LabelImg tool.
6. The data marking method as claimed in claim 1, wherein the step of cutting the video including at least one character and its apparel to obtain a plurality of pictures including the character and its apparel comprises:
cutting a video containing at least one character, clothes and accessories thereof to obtain a plurality of pictures containing the character, the clothes and the accessories thereof;
the step of guiding a plurality of pictures containing characters and clothes thereof into the labeling tool comprises the following steps:
leading a plurality of pictures containing characters, clothes and accessories thereof into a labeling tool;
the data marking method further comprises:
and utilizing a labeling tool to frame the accessory objects in each picture, and labeling the framed accessory objects according to the main category, the sub-category and the specific category.
7. The data marking method as claimed in claim 1 or 6, wherein the main category of the apparel comprises: upper outer garment, lower outer garment, footwear, headwear;
the subcategories of the jacket comprise a jacket, a shirt, a T-shirt, a vest and a suit, and the specific categories of the suit comprise a dovetail, a single-button suit, a double-button suit and a three-button suit; or
The sub-categories of the head wear category comprise a hat, a headband and glasses, and the specific categories of the glasses comprise presbyopic glasses, sunglasses and myopia glasses.
8. The data marking method as claimed in claim 6, wherein the main category of the accessory includes: upper garment accessories, lower garment accessories and hand accessories;
subcategories of the jacket accessory include a tie, a shawl, and a scarf; the specific types of the tie comprise a round tie, a triangular tie and a bow tie;
or the subcategories of the lower clothes accessories comprise belts and socks; specific classes of belts include cowhide belts, crocodile belts.
9. A computer device, characterized by: the computer arrangement comprises a processor for carrying out the steps of the data marking method as claimed in any one of claims 1 to 8 when executing a computer program stored in a memory.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program realizes the steps of the data marking method as claimed in any one of claims 1 to 8 when being executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811652805.9A CN111382747A (en) | 2018-12-29 | 2018-12-29 | Data marking method, computer device and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811652805.9A CN111382747A (en) | 2018-12-29 | 2018-12-29 | Data marking method, computer device and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111382747A true CN111382747A (en) | 2020-07-07 |
Family
ID=71218404
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811652805.9A Pending CN111382747A (en) | 2018-12-29 | 2018-12-29 | Data marking method, computer device and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111382747A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112732954A (en) * | 2020-12-31 | 2021-04-30 | 莱茵技术-商检（宁波）有限公司 | Intelligent labeling method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104951966A (en) * | 2015-07-13 | 2015-09-30 | 百度在线网络技术（北京）有限公司 | Clothes commodity recommending method and device |
| CN105469087A (en) * | 2015-07-13 | 2016-04-06 | 百度在线网络技术（北京）有限公司 | Method for identifying clothes image, and labeling method and device of clothes image |
| CN108229503A (en) * | 2018-01-04 | 2018-06-29 | 浙江大学 | A kind of feature extracting method for clothes photo |
| CN108229559A (en) * | 2017-12-29 | 2018-06-29 | 深圳市商汤科技有限公司 | Dress ornament detection method, device, electronic equipment, program and medium |
-
2018
- 2018-12-29 CN CN201811652805.9A patent/CN111382747A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104951966A (en) * | 2015-07-13 | 2015-09-30 | 百度在线网络技术（北京）有限公司 | Clothes commodity recommending method and device |
| CN105469087A (en) * | 2015-07-13 | 2016-04-06 | 百度在线网络技术（北京）有限公司 | Method for identifying clothes image, and labeling method and device of clothes image |
| CN108229559A (en) * | 2017-12-29 | 2018-06-29 | 深圳市商汤科技有限公司 | Dress ornament detection method, device, electronic equipment, program and medium |
| CN108229503A (en) * | 2018-01-04 | 2018-06-29 | 浙江大学 | A kind of feature extracting method for clothes photo |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112732954A (en) * | 2020-12-31 | 2021-04-30 | 莱茵技术-商检（宁波）有限公司 | Intelligent labeling method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11809393B2 (en) | Image and text data hierarchical classifiers | |
| CN109670591B (en) | Neural network training method and image matching method and device | |
| CN106126579B (en) | Object identification method and device, data processing device and terminal equipment | |
| CN108229559B (en) | Clothing detection method, clothing detection device, electronic device, program, and medium | |
| CN107861972A (en) | The method and apparatus of the full result of display of commodity after a kind of user's typing merchandise news | |
| CN109460512B (en) | Recommendation information processing method, device, equipment and storage medium | |
| WO2015135324A1 (en) | Picture sorting method and terminal | |
| CN106055710A (en) | Video-based commodity recommendation method and device | |
| JP2020522072A (en) | Fashion coordination recommendation method and device, electronic device, and storage medium | |
| KR102227896B1 (en) | System, method and program for obtaining appearance descriptive data from image data | |
| WO2019011936A1 (en) | Method for evaluating an image | |
| US20210264463A1 (en) | Creating Meta-Descriptors of Marketing Messages to Facilitate In Delivery Performance Analysis, Delivery Performance Prediction and Offer Selection | |
| CN114818710A (en) | Form information extraction method, device, equipment and medium | |
| Li et al. | Multi-label pattern image retrieval via attention mechanism driven graph convolutional network | |
| JP2024045510A (en) | Information processing device, information processing method, and program | |
| CN108764232B (en) | Label position obtaining method and device | |
| CN108833964B (en) | Real-time continuous frame information implantation identification system | |
| CN111382747A (en) | Data marking method, computer device and computer readable storage medium | |
| CN113762257A (en) | Identification method and device for marks in makeup brand images | |
| US20130236065A1 (en) | Image semantic clothing attribute | |
| CN111222000B (en) | Image classification method and system based on graph convolution neural network | |
| KR20200141387A (en) | System, method and program for searching image data by using deep-learning algorithm | |
| WO2020141802A2 (en) | Method for providing fashion item recommendation service to user by using date | |
| CN106446291A (en) | Method and apparatus for providing picture content pages based on artificial intelligence | |
| CN114332477A (en) | Feature recognition model training method, article feature recognition method and article feature recognition device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20211115 Address after: 518057 2nd floor, software building, No. 9, Gaoxin Zhongyi Road, Nanshan District, Shenzhen, Guangdong Applicant after: KUANG-CHI INSTITUTE OF ADVANCED TECHNOLOGY Address before: 310000 room 1101, building 14, No. 1008, yearning street, Cangqian street, Yuhang District, Hangzhou City, Zhejiang Province Applicant before: Hangzhou Guangqi Artificial Intelligence Research Institute |
|
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200707 |