mirror of
https://github.com/opencv/opencv.git
synced 2024-12-03 00:10:21 +08:00
0d3e05f9b3
[G-API Wrap streaming * Wrap streaming * Fix build * Add comments * Remove comment * Fix comments to review * Add test for python pull overload
130 lines
3.4 KiB
Python
130 lines
3.4 KiB
Python
#!/usr/bin/env python
|
|
|
|
import numpy as np
|
|
import cv2 as cv
|
|
import os
|
|
|
|
from tests_common import NewOpenCVTests
|
|
|
|
class test_gapi_streaming(NewOpenCVTests):
|
|
|
|
def test_image_input(self):
|
|
sz = (1280, 720)
|
|
in_mat = np.random.randint(0, 100, sz).astype(np.uint8)
|
|
|
|
# OpenCV
|
|
expected = cv.medianBlur(in_mat, 3)
|
|
|
|
# G-API
|
|
g_in = cv.GMat()
|
|
g_out = cv.gapi.medianBlur(g_in, 3)
|
|
c = cv.GComputation(g_in, g_out)
|
|
ccomp = c.compileStreaming(cv.descr_of(cv.gin(in_mat)))
|
|
ccomp.setSource(cv.gin(in_mat))
|
|
ccomp.start()
|
|
|
|
_, actual = ccomp.pull()
|
|
|
|
# Assert
|
|
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
|
|
|
|
|
def test_video_input(self):
|
|
ksize = 3
|
|
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
|
|
|
|
# OpenCV
|
|
cap = cv.VideoCapture(path)
|
|
|
|
# G-API
|
|
g_in = cv.GMat()
|
|
g_out = cv.gapi.medianBlur(g_in, ksize)
|
|
c = cv.GComputation(g_in, g_out)
|
|
|
|
ccomp = c.compileStreaming()
|
|
source = cv.gapi.wip.make_capture_src(path)
|
|
ccomp.setSource(source)
|
|
ccomp.start()
|
|
|
|
# Assert
|
|
while cap.isOpened():
|
|
has_expected, expected = cap.read()
|
|
has_actual, actual = ccomp.pull()
|
|
|
|
self.assertEqual(has_expected, has_actual)
|
|
|
|
if not has_actual:
|
|
break
|
|
|
|
self.assertEqual(0.0, cv.norm(cv.medianBlur(expected, ksize), actual, cv.NORM_INF))
|
|
|
|
|
|
def test_video_split3(self):
|
|
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
|
|
|
|
# OpenCV
|
|
cap = cv.VideoCapture(path)
|
|
|
|
# G-API
|
|
g_in = cv.GMat()
|
|
b, g, r = cv.gapi.split3(g_in)
|
|
c = cv.GComputation(cv.GIn(g_in), cv.GOut(b, g, r))
|
|
|
|
ccomp = c.compileStreaming()
|
|
source = cv.gapi.wip.make_capture_src(path)
|
|
ccomp.setSource(source)
|
|
ccomp.start()
|
|
|
|
# Assert
|
|
while cap.isOpened():
|
|
has_expected, frame = cap.read()
|
|
has_actual, actual = ccomp.pull()
|
|
|
|
self.assertEqual(has_expected, has_actual)
|
|
|
|
if not has_actual:
|
|
break
|
|
|
|
expected = cv.split(frame)
|
|
for e, a in zip(expected, actual):
|
|
self.assertEqual(0.0, cv.norm(e, a, cv.NORM_INF))
|
|
|
|
|
|
def test_video_add(self):
|
|
sz = (576, 768, 3)
|
|
in_mat = np.random.randint(0, 100, sz).astype(np.uint8)
|
|
|
|
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
|
|
|
|
# OpenCV
|
|
cap = cv.VideoCapture(path)
|
|
|
|
# G-API
|
|
g_in1 = cv.GMat()
|
|
g_in2 = cv.GMat()
|
|
out = cv.gapi.add(g_in1, g_in2)
|
|
c = cv.GComputation(cv.GIn(g_in1, g_in2), cv.GOut(out))
|
|
|
|
ccomp = c.compileStreaming()
|
|
source = cv.gapi.wip.make_capture_src(path)
|
|
ccomp.setSource(cv.gin(source, in_mat))
|
|
ccomp.start()
|
|
|
|
# Assert
|
|
while cap.isOpened():
|
|
has_expected, frame = cap.read()
|
|
has_actual, actual = ccomp.pull()
|
|
|
|
self.assertEqual(has_expected, has_actual)
|
|
|
|
if not has_actual:
|
|
break
|
|
|
|
expected = cv.add(frame, in_mat)
|
|
self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF))
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
NewOpenCVTests.bootstrap()
|