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Object Classification

Object localization is defined as a CNN, classifying a single object among several classes.

Content:

  • DogsVsCats.ipynb contains code for classifying a single animal (dog or cat) in an image.
  • predict.ipynb contains code for predicting any image for a cat or dog.
  • CNN_model.h5 is an internal database for storing the weight values of the trained CNN.

Packages:

  • Jupyter-Notebook (Python)
  • keras

Instructions:

  1. Download DogsVsCats.ipynb.ipynb
  2. Download predict.ipynb
  3. either download CNN_model.h5 to spare training and predict any cat or dog image with predict.ipynb or download dataset for own training. The source of the image datasets: https://www.kaggle.com/
  4. Make sure to edit the pwd for the data(sub)sets
  5. Run code

Object Localization

Object localization is defined as a CNN, classifying a single object among several classes and drawing a single bounding box around that object.

Content:

  • Dogs_vs_Cats_Localization_functional.ipynb contains code for classifying a single animal (dog or cat) in an image and drawing a bouding box around it.

Packages:

  • Jupyter-Notebook (Python)
  • numpy
  • PIL
  • tensorflow
  • keras
  • matplotlib
  • xml

Instructions:

  1. Download Dogs_vs_Cats_Localization_functional.ipynb
  2. Download dataset. The source of the image datasets: https://www.robots.ox.ac.uk/~vgg/data/pets/ Caution: I noticed, images and labels might be corrupted in its chronology!
  3. Make sure to edit the pwd for the data(sub)sets
  4. Run code