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Last pushed: 5 days ago
Short Description
jupyter/scipy-notebook, plus OpenCV 3.0.0, Python 3 bindings, and the OpenCV extra modules.
Full Description

mciantyre/scipy-opencv-notebook Docker image

All the fun of the jupyter/scipy-notebook Docker image, plus OpenCV 3.0.0, Python 3 bindings, and the OpenCV extra modules. Check out the jupyter/scipy-notebook for more information.

Note: OpenCV was built with only Python 3 bindings. Therefore, Python 2 notebooks cannot import cv2.

Getting started

docker pull mciantyre/scipy-opencv-notebook
docker run -d -p 8888:8888 mciantyre/scipy-opencv-notebook

See jupyter/scipy-notebook for optional run arguments.

Navigate to localhost:8888 in any browser, and make your first Python 3 notebook! Here's a script to find a face in a picture that you upload:

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import cv2

img = cv2.imread("your_uploaded_image.jpg")
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.imshow(img)        # shows face without box

# If you need to find directories of data files,
# open up a terminal window from the web interface and search from there
#    find /opt -iname *haar*
face_cascade = cv2.CascadeClassifier('/opt/opencv/data/haarcascades/haarcascade_frontalface_default.xml')

faces = face_cascade.detectMultiScale(img, 1.1, 3)
for (x,y,w,h) in faces:
    roi = img[y:y+h, x:x+w]

plt.imshow(img)        # shows the face with a box around it

Doesn't this exist?

In a few places! But, I wanted to make my own for practice.

Thanks to the jupyter/docker-stacks project and the Jupyter team, OpenCV, and Docker. Made for the University of Pittsburgh DesignHub.

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