Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

369 lines
11 KiB

#!/usr/bin/env python
import numpy as np
import cv2 as cv
import os
import sys
import unittest
import time
from tests_common import NewOpenCVTests
try:
if sys.version_info[:2] < (3, 0):
raise unittest.SkipTest('Python 2.x is not supported')
@cv.gapi.op('custom.delay', in_types=[cv.GMat], out_types=[cv.GMat])
class GDelay:
"""Delay for 10 ms."""
@staticmethod
def outMeta(desc):
return desc
@cv.gapi.kernel(GDelay)
class GDelayImpl:
"""Implementation for GDelay operation."""
@staticmethod
def run(img):
time.sleep(0.01)
return img
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.gapi.descr_of(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(cv.gin(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(cv.gin(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(cv.gin(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(),
np.array(a, np.float32).flatten(),
cv.NORM_INF))
proc_num_frames += 1
if proc_num_frames == max_num_frames:
break
def test_gapi_streaming_meta(self):
ksize = 3
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
# G-API
g_in = cv.GMat()
g_ts = cv.gapi.streaming.timestamp(g_in)
g_seqno = cv.gapi.streaming.seqNo(g_in)
g_seqid = cv.gapi.streaming.seq_id(g_in)
c = cv.GComputation(cv.GIn(g_in), cv.GOut(g_ts, g_seqno, g_seqid))
ccomp = c.compileStreaming()
source = cv.gapi.wip.make_capture_src(path)
ccomp.setSource(cv.gin(source))
ccomp.start()
# Assert
max_num_frames = 10
curr_frame_number = 0
while True:
has_frame, (ts, seqno, seqid) = ccomp.pull()
if not has_frame:
break
self.assertEqual(curr_frame_number, seqno)
self.assertEqual(curr_frame_number, seqid)
curr_frame_number += 1
if curr_frame_number == max_num_frames:
break
def test_desync(self):
path = self.find_file('cv/video/768x576.avi', [os.environ['OPENCV_TEST_DATA_PATH']])
# G-API
g_in = cv.GMat()
g_out1 = cv.gapi.copy(g_in)
des = cv.gapi.streaming.desync(g_in)
g_out2 = GDelay.on(des)
c = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out1, g_out2))
kernels = cv.gapi.kernels(GDelayImpl)
ccomp = c.compileStreaming(args=cv.gapi.compile_args(kernels))
source = cv.gapi.wip.make_capture_src(path)
ccomp.setSource(cv.gin(source))
ccomp.start()
# Assert
max_num_frames = 10
proc_num_frames = 0
out_counter = 0
desync_out_counter = 0
none_counter = 0
while True:
has_frame, (out1, out2) = ccomp.pull()
if not has_frame:
break
if not out1 is None:
out_counter += 1
if not out2 is None:
desync_out_counter += 1
else:
none_counter += 1
proc_num_frames += 1
if proc_num_frames == max_num_frames:
ccomp.stop()
break
self.assertLess(0, proc_num_frames)
self.assertLess(desync_out_counter, out_counter)
self.assertLess(0, none_counter)
def test_compile_streaming_empty(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
comp.compileStreaming()
def test_compile_streaming_args(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
comp.compileStreaming(cv.gapi.compile_args(cv.gapi.streaming.queue_capacity(1)))
def test_compile_streaming_descr_of(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
img = np.zeros((3,300,300), dtype=np.float32)
comp.compileStreaming(cv.gapi.descr_of(img))
def test_compile_streaming_descr_of_and_args(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
img = np.zeros((3,300,300), dtype=np.float32)
comp.compileStreaming(cv.gapi.descr_of(img),
cv.gapi.compile_args(cv.gapi.streaming.queue_capacity(1)))
def test_compile_streaming_meta(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
img = np.zeros((3,300,300), dtype=np.float32)
comp.compileStreaming([cv.GMatDesc(cv.CV_8U, 3, (300, 300))])
def test_compile_streaming_meta_and_args(self):
g_in = cv.GMat()
comp = cv.GComputation(g_in, cv.gapi.medianBlur(g_in, 3))
img = np.zeros((3,300,300), dtype=np.float32)
comp.compileStreaming([cv.GMatDesc(cv.CV_8U, 3, (300, 300))],
cv.gapi.compile_args(cv.gapi.streaming.queue_capacity(1)))
except unittest.SkipTest as e:
message = str(e)
class TestSkip(unittest.TestCase):
def setUp(self):
self.skipTest('Skip tests: ' + message)
def test_skip():
pass
pass
if __name__ == '__main__':
NewOpenCVTests.bootstrap()