def templateMatching(im,elements, isPhoto):
templates = ['images/templates/resistorT4.PNG', 'images/templates/resistorT2.PNG', 'images/templates/resistorT2_0degree.PNG', 'images/templates/resistorT2_45degree.PNG', 'images/templates/resistorT2_135degree.PNG','images/templates/resistorT4_0degree.PNG'];
unmatched_resistors = [];
for elem in elements:
if elem[4] == 'o':
unmatched_resistors += [elem];
matched_resistors = {}
matched_resistor_key = {}
for threshold in [1, .9, .8, .7, .6, .5]:#, .5, .4, .3]:
for restt in range(2, 15):
for t in templates:
templ = cv2.imread(t,cv2.CV_LOAD_IMAGE_COLOR);
res = 20 - restt;
template = cv2.resize(templ, dsize = (0,0), fx = res/10., fy = res/10., interpolation = cv2.INTER_CUBIC);
[template, g]= Preprocess.getImageToSendToContour(template, False);
w, h = template.shape[::-1]
res = cv2.matchTemplate(im,template,cv2.TM_CCOEFF_NORMED)
loc = np.where( res >= threshold)
pts = []
for pt in zip(*loc[::-1]):
pts += [[pt[0], pt[1], w, h, 'r']];
indicesToRemove_ii = []
indicesToRemove_i = []
for i in range(0, len(unmatched_resistors)):
ii = -1;
minDistance = 1000000;
for ifindmin in range(0,len(pts)):
dist = Postprocess.distance_resistor(unmatched_resistors[i][0:5], pts[ifindmin]);
if dist < minDistance and (ifindmin not in indicesToRemove_ii) and dist < 20 and dist < matched_resistor_key.get(i, 10000)*(threshold*1.1) and dist>7:
ii = ifindmin;
minDistance = dist;
if ii == -1:
continue;
matchresistor = unmatched_resistors[i][:];
matchresistor[0] = pts[ii][0]; #take on location of the element in the circuit
matchresistor[1] = pts[ii][1];
matchresistor[2] = pts[ii][2];
matchresistor[3] = pts[ii][3];
indicesToRemove_ii += [ii];
indicesToRemove_i += [i];
matched_resistors[i] = matchresistor;
matched_resistor_key[i] = dist;
#newunmatched = []
#for i in range(0, len(unmatched_resistors)):
# if i not in indicesToRemove_i:
# newunmatched += [unmatched_resistors[i]]
#unmatched_resistors = newunmatched;
# for r in matched_resistors:
# print r
print matched_resistors
print unmatched_resistors
for i in matched_resistors.keys():
pt = matched_resistors[i];
cv2.rectangle(im, (pt[0], pt[1]), (pt[0] + pt[2], pt[1] + pt[3]), (0,0,0), 2)
matchresistor = unmatched_resistors[i];
matchresistor[0] = pt[0]; #take on location of the element in the circuit
matchresistor[1] = pt[1];
matchresistor[2] = pt[2];
matchresistor[3] = pt[3];
cv2.imshow('resistors', im);
# cv2.imshow('temp', template);
# key = cv2.waitKey(0)
return elements;
#cv2.rectangle(im, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
import cv2
import numpy as np
from matplotlib import pyplot as plt
import Preprocess;
#http://docs.opencv.org/trunk/doc/py_tutorials/py_imgproc/py_template_matching/py_template_matching.html#py-template-matching
#works, but only if the template size is same as size of object in the query image.
img_rgb = cv2.imread('images/photo3cropped.jpg',cv2.CV_LOAD_IMAGE_COLOR)
img_rgb = cv2.resize(img_rgb, dsize = (0,0), fx = .1, fy = .1, interpolation = cv2.INTER_CUBIC);
[img_gray, gray] = Preprocess.getImageToSendToContour(img_rgb, True);
#img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
templates = ['images/resistorT4.PNG', 'images/resistorT2.PNG', 'images/resistorT2_0degree.PNG', 'images/resistorT4_0degree.PNG'];
print img_gray;
for t in templates:
templ = cv2.imread(t,cv2.CV_LOAD_IMAGE_COLOR);
for res in range(6, 15):
template = cv2.resize(templ, dsize = (0,0), fx = res/10., fy = res/10., interpolation = cv2.INTER_CUBIC);
[template, g]= Preprocess.getImageToSendToContour(template, False);
w, h = template.shape[::-1]
res = cv2.matchTemplate(img_gray,template,cv2.TM_CCOEFF_NORMED)
threshold = 0.4
loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]):
cv2.rectangle(img_gray, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
cv2.imshow('template', template)
