• Slides
• Notebook

• Notebook

• Notebook

• Slides
• Notebook

• Slides
• Notebook

• Slides
• Notebook

• Notebook

• Slides
• Notebook - Parte 1
• Notebook - Parte 1 - Colab
• Notebook - Parte 2
• Notebook - Parte 2 - Colab

• Slides
• Notebook - Parte 1
• Notebook - Parte 2

• Slides
• Notebook

• instalar o Anaconda Distribution

• Criar um ambiente de execução virtual

  $ conda create -n sin393-2022-py38 python=3.8

  $ conda activate sin393-2022-py38

• Instalar as bibliotecas necessárias

  $ conda install numpy scikit-image scikit-learn matplotlib pandas seaborn notebook

  $ pip install opencv-python

• PyTorch.

  • Instalação no Ubuntu com GPU.
  • Para instalação no Windows ou sem GPU, consultar pytorch.org.

  $ conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia

  $ pip install -U albumentations

• GONZALEZ, R.C.; WOODS, R.E. Processamento de Imagens Digitais. 3. ed. Pearson, 2010.
• COSTA, L.F.; CÉSAR-JR., R.M. Shape analysis and classification: Theory and practice. 1. ed. CRC Press, 2000.
• RUSSEL, S.J.; NORVIG, P. Inteligência Artificial. 2.ed. Campus, 2004.
• DUDA, R.O.; HART, P.E.; STORK, D.G. Pattern Classification. Wiley, 2001.
• CHITYALA, R.; PUDIPEDDI, S. Image processing and acquisition using Python. CRC Press, 2014.
• MARQUES FILHO, O.; VIEIRA NETO, H. Processamento digital de imagens. Brasport, 1999.
  • http://dainf.ct.utfpr.edu.br/~hvieir/pub.html
• PONTI, M. Everything you wanted to know about Deep Learning for Computer Vision but were afraid to ask. SIBGRAPI 2017 Tutorial.
  • http://conteudo.icmc.usp.br/pessoas/moacir/p17sibgrapi-tutorial/
• PONTI, M; COSTA, G. B. P. Como funciona o Deep Learning. Computer Vision and Pattern Recognition. 2017.
  • https://arxiv.org/abs/1806.07908
• CS231n: Convolutional Neural Networks for Visual Recognition.
  • http://cs231n.stanford.edu/
• GOODFELLOW, I.; BENGIO, Y.; COURVILLE, A. Deep Learning. MIT Press, 2016.
  • http://www.deeplearningbook.org
• NIELSEN, M. Neural Networks and Deep Learning. Livro On-Line.
  • http://neuralnetworksanddeeplearning.com

• Anaconda Distribution
  • https://www.anaconda.com/distribution/
• Google Colab
  • https://colab.research.google.com
• Scikit-image
  • https://scikit-image.org/
• Scikit-learn
  • https://scikit-learn.org/
• OpenCv
  • https://opencv.org/
  • Binding para Python:
    • https://pypi.org/project/opencv-python/
    • https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html
• PyTorch
  • https://pytorch.org/

• 2018-2
• 2019-2

• Como citar este material:

    @misc{mari_comp_vis_2022,
        author = {João Fernando Mari},
        title = {Introdução à visão computacional},
        year = {2022},
        publisher = {GitHub},
        journal = {GitHub repository},
        howpublished = {\url{https://github.com/joaofmari/SIN393_Introducao-a-visao-computacional_2022-2}}
    }

João Fernando Mari - UFV-CRP - 2022-2 - joaofmari.github.io - joaof.mari@ufv.br