Created
April 6, 2016 20:10
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import base64 as b64 | |
import numpy as np | |
import cv2 | |
import matplotlib.pyplot as plt | |
from ipywidgets import interact, interactive, fixed | |
from IPython.display import Image, display | |
import ipywidgets as widgets | |
def convert_media_to_image(media): | |
arr = np.asarray(bytearray(b64.b64decode(media["__data__"])), dtype=np.uint8) | |
return cv2.imdecode(arr,-1) | |
history = 50 | |
nGauss = 2 | |
bgThresh = 0.75 | |
noise = 20 | |
fgbg = cv2.BackgroundSubtractorMOG(history, nGauss, bgThresh, noise) | |
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(4,4)) | |
def preprocess(image, ref): | |
fgmask = fgbg.apply(image) | |
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel) | |
return fgmask | |
def display_image(image): | |
_, png_image = cv2.imencode(".png", image) | |
display(Image(data=png_image.tostring())) | |
images = [convert_media_to_image(rec["media"]) for oid, rec in data] | |
shape = list(images[0].shape) | |
shape.append(min(len(images), 100)) | |
avg = np.zeros(shape) | |
for z, image in enumerate(images[:100]): | |
avg[:,:,:,z] = image | |
avg = np.uint8(np.average(avg, axis=3)) | |
avg = cv2.merge([avg[:,:,0],avg[:,:,1],avg[:,:,2]]) | |
fgbg.apply(avg) | |
preprocessed = [preprocess(img, avg) for img in images] | |
cv2.imwrite("avg.jpg", avg) | |
@interact(idx=widgets.IntSlider(min=0,max=len(images)-1,step=1,value=0)) | |
def display_contours(idx): | |
contours, _ = cv2.findContours(preprocessed[idx],cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) | |
areas = [cv2.contourArea(c) for c in contours] | |
good_contours = [c for c, a in zip(contours, areas) if a < 200] | |
cv2.drawContours(images[idx], good_contours, -1, (0, 0, 255)) | |
display_image(images[idx]) | |
print "%i 'people' found" % len(good_contours) |
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