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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-machine-learning-optical-character-recognition-golang/
课程评论：没有评论
课程名称：如何构建AI与机器学习识别应用 课程概述： 本课程通过使用视觉API，教您如何从图像中检测和提取文本。该API提供两种支持光学字符识别的注释功能：TEXT_DETECTION和DOCUMENT_TEXT_DETECTION。TEXT_DETECTION可以从任何图像中检测并提取文本，例如街道标志或交通标志，返回整个提取的字符串、单词及其边界框信息。而DOCUMENT_TEXT_DETECTION则针对密集文本和文档进行优化提取，返回页面、块、段落、单词及换行信息。 在计算机视觉方面，本课程将展示如何从图像中提取丰富的信息，以便分类和处理视觉数据，并执行图像的机器辅助审核来帮助您策划服务。您还将学习如何分析图像，获取视觉内容信息，使用标记、特定领域模型以及四种语言的描述来识别内容并自信地标记。通过对象检测技术，您可以获得图像中成千上万物体的位置，并应用成人内容/敏感内容设置，以帮助检测潜在的成人内容。同时，您还将能够识别图像类型和色彩方案，及识别超过200,000名名人和9,000个来自世界各地的自然及人造地标。 在面部识别方面，本课程将介绍如何检测和比较人类面孔，并基于相似性对图像进行分组。您将学习如何识别先前标记过的人物，并在本地或云端运行这些功能。课程将覆盖面部验证码、面部检测及其属性预测，包括年龄、情绪、性别、姿势、微笑和面部毛发等信息，以及进行情绪识别，返回每张面孔在愤怒、轻蔑、厌恶、恐惧、幸福、中立、悲伤和惊讶等一系列情绪上的自信度。 通过本课程，您将掌握如何利用先进的识别技术构建AI与机器学习应用，提升图像处理和分析的能力。
The Vision API can detect and extract text from images. There are two annotation features that support optical character recognition:TEXT_DETECTION detects and extracts text from any image. For example, a photograph might contain a street sign or traffic sign. The JSON includes the entire extracted string, as well as individual words, and their bounding boxes.DOCUMENT_TEXT_DETECTION also extracts text from an image, but the response is optimized for dense text and documents. The JSON includes page, block, paragraph, word, and break information.Computer VisionExtract rich information from images to categorize and process visual data-and perform machine-assisted moderation of images to help curate your services.Analyze an imageThis feature returns information about visual content found in an image. Use tagging, domain-specific models, and descriptions in four languages to identify content and label it with confidence. Use Object Detection to get location of thousands of objects within an image. Apply the adult/racy settings to help you detect potential adult content. Identify image types and color schemes in pictures.Recognize celebrities and landmarksRecognize more than 200,000 celebrities from business, politics, sports and entertainment, as well as 9,000 natural and manmade landmarks from around the world.FaceDetect and compare human facesOrganize images into groups based on similaritiesIdentify previously tagged people in imagesRun locally on-premises or in the cloudFace verificationCheck the likelihood that two faces belong to the same person. The API will return a confidence score about how likely it is that the two faces belong to one person.Face detectionDetect one or more human faces in an image and get back face rectangles for where in the image the faces are, along with face attributes which contain machine learning-based predictions of facial features. The face attribute features available are: Age, Emotion, Gender, Pose, Smile, and Facial Hair along with 27 landmarks for each face in the image.Emotion recognitionThe Face API now integrates emotion recognition, returning the confidence across a set of emotions for each face in the image such as anger, contempt, disgust, fear, happiness, neutral, sadness, and surprise. These emotions are understood to be cross-culturally and universally communicated with particular facial expressions.
