Python EZSiftImageMatcherの例

コード例 #1

ファイル: ezsift_real_test.py プロジェクト: hendrikvgl/RoboCup-Spielererkennung

    def test_list_flattening(self):
        ezsift_matcher = EZSiftImageMatcher()

        logo_1 = "example.png"
        image = cv2.imread(os.path.abspath(logo_1))
        grey_scale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        grey_scale_image_1 = np.array(grey_scale_image)
        ezsift_matcher.add_reference_image(logo_1, grey_scale_image_1)

        logo_2 = "logo2.png"
        image = cv2.imread(os.path.abspath(logo_2))
        grey_scale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        grey_scale_image_2 = np.array(grey_scale_image)
        ezsift_matcher.add_reference_image(logo_2, grey_scale_image_2)

        real_photo = "index.png"
        image = cv2.imread(os.path.abspath(real_photo))
        grey_scale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        grey_scale_image_3 = np.array(grey_scale_image)

        print ezsift_matcher.match(grey_scale_image_3)

コード例 #2

ファイル: embedding.py プロジェクト: hendrikvgl/RoboCup-Spielererkennung

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import itertools
import cv2
from sklearn import manifold
from ezsift_wrapper import EZSiftImageMatcher
from embedding_data import StudyImageMDSVisualizer2D
import numpy as np
import matplotlib.pyplot as plt

color_cycle = itertools.cycle([[255, 0, 0], [0, 255, 0], [0, 255, 0]])

ezsift_matcher = EZSiftImageMatcher()

num_images = 100

for i in range(0, num_images, 1):
    path = "./img/image-{}.png".format(i)
    print path
    img1 = cv2.imread(path)
    g1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
    ezsift_matcher.add_reference_image(str(i), g1)


conf_matrix = ezsift_matcher.get_reference_image_confusion_matrix()

np_conf_mat = np.array(conf_matrix)


for i in range(num_images):
    for j in range(num_images):

コード例 #3

ファイル: pyexampe3.py プロジェクト: hendrikvgl/RoboCup-Spielererkennung

logo_1 = "left.png"
image = misc.imread(logo_1, flatten=True) #cv2.imread(os.path.abspath(logo_1))
import matplotlib.pyplot as plt
#grey_scale_image1 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#grey_scale_image1 = np.array(grey_scale_image1)
ezsift_matcher.add_reference_image(logo_1, image)

logo_2 = "feld.png"
image = misc.imread(logo_2, flatten=True) #cv2.imread(os.path.abspath(logo_2))
#grey_scale_image2 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#grey_scale_image2 = np.array(grey_scale_image2)
ezsift_matcher.add_reference_image(logo_2, image)
"""


ezsift_matcher = EZSiftImageMatcher()

# ML Capture Part:

vidgrab = VideoGrabber(1)


angles_to_capture = [90, 45, 0, -45, -90]
current = 0

cap = True
while cap:

    gray = vidgrab.grab_frame_return_grey()
    grey_scale_image = cv2.cvtColor(gray, cv2.COLOR_BGR2GRAY)
    grey_scale_image = np.array(grey_scale_image)

コード例 #4

ファイル: pyexampe.py プロジェクト: hendrikvgl/RoboCup-Spielererkennung

import itertools
from scipy import misc

__author__ = 'sheepy'

from ezsift_wrapper import EZSiftImageMatcher
import scipy.misc
from fileimagegrabber import ImageFromFileGrabber

color_cycle = itertools.cycle([[255,0,0], [0, 255, 0]])


video_grabber = ImageFromFileGrabber(os.path.abspath("data/"))


ezsift_matcher = EZSiftImageMatcher()


logo_1 = "left.png"
image = misc.imread(logo_1, flatten=True) #cv2.imread(os.path.abspath(logo_1))
import matplotlib.pyplot as plt
#grey_scale_image1 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#grey_scale_image1 = np.array(grey_scale_image1)
ezsift_matcher.add_reference_image(logo_1, image)

logo_2 = "feld.png"
image = misc.imread(logo_2, flatten=True) #cv2.imread(os.path.abspath(logo_2))
#grey_scale_image2 = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#grey_scale_image2 = np.array(grey_scale_image2)
ezsift_matcher.add_reference_image(logo_2, image)