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#!/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
max_num_frames = 10
proc_num_frames = 0
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))
proc_num_frames += 1
if proc_num_frames == max_num_frames:
break;
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
max_num_frames = 10
proc_num_frames = 0
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))
proc_num_frames += 1
if proc_num_frames == max_num_frames:
break;
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
max_num_frames = 10
proc_num_frames = 0
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))
proc_num_frames += 1
if proc_num_frames == max_num_frames:
break;
def test_video_good_features_to_track(self):
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
# NB: goodFeaturesToTrack configuration
max_corners = 50
quality_lvl = 0.01
min_distance = 10
block_sz = 3
use_harris_detector = True
k = 0.04
mask = None
# OpenCV
cap = cv.VideoCapture(path)
# G-API
g_in = cv.GMat()
g_gray = cv.gapi.RGB2Gray(g_in)
g_out = cv.gapi.goodFeaturesToTrack(g_gray, max_corners, quality_lvl,
min_distance, mask, block_sz, use_harris_detector, k)
c = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out))
ccomp = c.compileStreaming()
source = cv.gapi.wip.make_capture_src(path)
ccomp.setSource(source)
ccomp.start()
# Assert
max_num_frames = 10
proc_num_frames = 0
while cap.isOpened():
has_expected, frame = cap.read()
has_actual, actual = ccomp.pull()
self.assertEqual(has_expected, has_actual)
if not has_actual:
break
# OpenCV
frame = cv.cvtColor(frame, cv.COLOR_RGB2GRAY)
expected = cv.goodFeaturesToTrack(frame, max_corners, quality_lvl,
min_distance, mask=mask,
blockSize=block_sz, useHarrisDetector=use_harris_detector, k=k)
for e, a in zip(expected, actual):
# NB: OpenCV & G-API have different output shapes:
# OpenCV - (num_points, 1, 2)
# G-API - (num_points, 2)
self.assertEqual(0.0, cv.norm(e.flatten(), a.flatten(), cv.NORM_INF))
proc_num_frames += 1
if proc_num_frames == max_num_frames:
break;
if __name__ == '__main__':
NewOpenCVTests.bootstrap()
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