This course will walk you through a hands-on project suitable for a portfolio. You will be introduced to third-party APIs and will be shown how to manipulate images using the Python imaging library (pillow), how to apply optical character recognition to images to recognize text (tesseract and py-tesseract), and how to identify faces in images using the popular opencv library. By the end of the course you will have worked with three different libraries available for Python 3 to create a real-world data-analysis project.
Este curso faz parte do Programa de cursos integrados Python 3 Programming
Python Project: pillow, tesseract, and opencv
oferecido por
Informações sobre o curso
100,963 visualizações recentes
O que você vai aprender
How to inspect and understand APIs and third party libraries to be used with Python 3
How to apply the Python imaging library (pillow) to open, view, and manipulate images, including cropping, resizing, recoloring, and overlaying text
How to apply the python tesseract (py-tesseract) library with Python 3 in order to detect text in images through optical character recognition (OCR)
How to apply the open source computer vision library (opencv) to detect faces in images, & how to crop and manipulate these faces into contact sheets
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 5 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 13 horas para completar
Sugerido: 13 hours/week
Inglês
Legendas: Inglês
Programa - O que você aprenderá com este curso
6 horas para concluir
The Python Imaging Library
6 horas para concluir
10 vídeos (Total 73 mín.), 1 leitura, 1 teste
10 videos
Welcome to Python Project: pillow, tesseract, opencv3min
Introduction to Jupyter Notebooks6min
How to install Jupyter on Windows (Optional)8min
How to install Jupyter on a Mac (Optional)8min
The Python Runtime Environment4min
Python Imaging Library (PIL)7min
Common Functions in the Python Imaging Library8min
Additional PIL Functions11min
Introduction to Week One Assignment2min
1 leituras
Syllabus10min
2 horas para concluir
Tesseract and Optical Character Recognition
2 horas para concluir
6 vídeos (Total 41 mín.)
6 videos
Open-Source Software4min
The (Py)Tesseract Library7min
More Tesseract11min
Tesseract and Photographs11min
Jupyter Widgets (Optional)3min
14 horas para concluir
Computer Vision with OpenCV
14 horas para concluir
4 vídeos (Total 51 mín.), 4 leituras, 1 teste
4 videos
Release the Kraken!17min
Comparing Image Data Structures12min
OpenCV17min
More Jupyter Widgets (Optional)3min
4 leituras
Hint 110min
Hint 210min
Hint 310min
Hint 410min
Avaliações
Principais avaliações do PYTHON PROJECT: PILLOW, TESSERACT, AND OPENCV
por RKMay 4, 2019
V\n\na\n\ne\n\nr\n\ny\n\nG\n\no\n\no\n\nd\n\ns\n\np\n\ne\n\nc\n\ni\n\na\n\nl\n\ni\n\nz\n\na\n\nt\n\ni\n\no\n\nn\n\nf\n\no\n\nr\n\np\n\ny\n\nt\n\nh\n\no\n\nn\n\n3
por UAJul 30, 2019
It's very interesting the assignment and the final project. But maybe you should think of changing the Jupiter notebook. It doesn't work correctly very often.
por STNov 8, 2019
It's not an easy course but it was well worth the effort. I learned a lot about pillow, tesseract and OpenCV.
por MKJan 26, 2020
Pretty good to get the Python Basics before getting on with advanced Python (or ML) programming.
por DBJun 17, 2019
Not much details on the course but good for starters in the field of computer vision
por SKFeb 9, 2020
It was really helpful. Moreover, this course teaches us how to learn ourselves.
por ECJan 26, 2020
Interesting course, but Coursera's Jupyter environment isn't very robust.
por CAJul 30, 2019
Should have been a more detailed lecture. Covering things more slowly.
por NFJun 2, 2019
A better way to submit the code for the last project is needed.
por CCMar 17, 2020
Great and detailed, lots of useful exercises and clear videos.
por CCMar 10, 2020
Great course! It is more challenging than previous ones.
oferecido por
Universidade de Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Sobre Programa de cursos integrados Python 3 Programming
This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance.
You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work.
By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer.
This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python.
But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Qual é a política de reembolso?
Existe algum auxílio financeiro disponível?
Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.