Over 20,000 pictures of cats and dogs in different enviroments. Dataset available at: microsoft.com/en-us/download/details.aspx?id=54765.
- Tensorflow-gpu
- OpenCV
- Scikit-Learn
- Pandas
- NumPy
- Matplotlib
- tqdm
The Convolutional Neural Network gained popularity through its use with image data, and is currently the state of the art for detecting what an image is, or what is contained in the image. The basic CNN structure is as follows: Convolution -> Pooling -> Convolution -> Pooling -> Fully Connected Layer -> Output
Convolution is the act of taking the original data, and creating feature maps from it.Pooling is down-sampling, most often in the form of "max-pooling," where we select a region, and then take the maximum value in that region, and that becomes the new value for the entire region. pythonprogramming.net
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git clone https://github.com/rezan21/Cat-Dog-Classifier.git
or Download the repository and unzip it -
Install required libraries
- Make sure all specified libraries are installed, if not, use
pip install
.
- Make sure all specified libraries are installed, if not, use
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Run Jupyter lab or notebook and open
cat_dogs_cnn.ipynb
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Apply following changes to the code
- delete/comment first 3 lines of the first cell
- change first line of the second cell to match the location where the dataset you downloaded is stored:
- On mac:
DATADIR = '/Users/YOUR_USER_HERE/Downloads/Cat-Dog-Classifier-master/catsanddogs'
- On mac:
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Run remaning cells