providers:sru: New provider including SRU specific units

- The SRU testplan - The opencv screenshot validation jobs and binary Moving those tests out from the checkbox provider will avoid having tests requiring python2.7 (since screenshot validation is only used for SRU) 

1 files changed, 0 insertions, 161 deletions

diff --git a/bin/screenshot_validation b/bin/screenshot_validation
deleted file mode 100755
index 5529f799..00000000
--- a/bin/screenshot_validation
+++ /dev/null
@@ -1,161 +0,0 @@
-#!/usr/bin/env python2.7
-# Copyright 2014 Canonical Ltd.
-# Written by:
-# Sylvain Pineau <sylvain.pineau@canonical.com>
-#
-# This program is free software: you can redistribute it and/or modify
-# it under the terms of the GNU General Public License version 3,
-# as published by the Free Software Foundation.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program. If not, see <http://www.gnu.org/licenses/>.
-
-from __future__ import absolute_import, print_function
-
-import argparse
-import imghdr
-import os
-
-import cv2
-
-
-def create_capture(args):
- try:
- device_no = int(os.path.realpath(args.device)[-1])
- except ValueError:
- raise SystemExit(
- "ERROR: video source not found: {}".format(args.device))
- cap = cv2.VideoCapture(device_no)
- # The camera driver will adjust the capture size
- cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, args.width)
- cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, args.height)
- if cap is None or not cap.isOpened():
- raise SystemExit(
- "ERROR: unable to open video source: {}".format(args.device))
- return cap
-
-parser = argparse.ArgumentParser(
- description='''
-Automatically validates a screenshot captured with an external camera using
-OpenCV ORB detection and a FLANN Matcher (Fast Approximate Nearest Neighbor
-Search Library)
-
-Put your camera (HD recommended) in front of your monitor.
-A query image (the INPUT positional argument) is displayed on your primary
-device and several captures (see -F) are analyzed to find a positive match.
-
-On success returns 0. Otherwise a non-zero value is returned and a
-diagnostic message is printed on standard error.
-''',
- formatter_class=argparse.RawDescriptionHelpFormatter
-)
-parser.add_argument('input',
- metavar='INPUT',
- help='Input file to use as query image')
-parser.add_argument('--min_matches',
- type=int,
- default=20,
- help='Minimum threshold value to validate a \
- positive match')
-parser.add_argument('-F', '--frames',
- type=int,
- default=10,
- help='Set the number of frames to capture and analyze \
- Minimum: 3')
-parser.add_argument('-d', '--device',
- default='/dev/video0',
- help='Set the device to use')
-parser.add_argument('--height',
- type=int,
- default=900,
- help='Set the capture height')
-parser.add_argument('--width',
- type=int,
- default=1600,
- help='Set the capture width')
-parser.add_argument('-o', '--output',
- default=None,
- help='Save the screenshot to the specified filename')
-args = parser.parse_args()
-
-if args.frames < 3:
- parser.print_help()
- raise SystemExit(1)
-if not imghdr.what(args.input):
- raise SystemExit(
- "ERROR: unable to read the input file: {}".format(args.input))
-queryImage = cv2.imread(args.input, cv2.CV_LOAD_IMAGE_GRAYSCALE)
-
-cv2.namedWindow("test", cv2.WND_PROP_FULLSCREEN)
-cv2.setWindowProperty("test",
- cv2.WND_PROP_FULLSCREEN,
- cv2.cv.CV_WINDOW_FULLSCREEN)
-cv2.imshow("test", queryImage)
-cv2.waitKey(1000)
-
-# Initiate ORB features detector
-orb = cv2.ORB(nfeatures=100000)
-
-# Find the keypoints and descriptors with ORB
-kp1, des1 = orb.detectAndCompute(queryImage, None)
-
-# Use the FLANN Matcher (Fast Approximate Nearest Neighbor Search Library)
-flann_params = dict(algorithm=6, # FLANN_INDEX_LSH
- table_number=6,
- key_size=12,
- multi_probe_level=1)
-
-flann = cv2.FlannBasedMatcher(flann_params, {})
-
-source = 0
-cap = create_capture(args)
-results = []
-img = None
-
-for i in range(args.frames):
-
- ret, img = cap.read()
- if ret is False:
- raise SystemExit(
- "ERROR: unable to capture from video source: {}".format(source))
- trainImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-
- # Find the keypoints and descriptors with ORB
- kp2, des2 = orb.detectAndCompute(trainImage, None)
- if des2 is None:
- raise SystemExit(
- "ERROR: Not enough keypoints in video capture, aborting...")
-
- matches = flann.knnMatch(des1, des2, k=2)
-
- # store all the good matches as per Lowe's ratio test
- good_matches = [m[0] for m in matches if len(m) == 2 and
- m[0].distance < m[1].distance * 0.7]
-
- results.append(len(good_matches))
- cv2.waitKey(1000)
-
-cv2.destroyAllWindows()
-
-if args.output:
- cv2.imwrite(args.output, img)
- print('Screenshot saved to: {}'.format(args.output))
-
-# Remove Max and Min values from results
-results.remove(max(results))
-results.remove(min(results))
-
-avg = sum(results) / len(results)
-
-if avg > args.min_matches:
- print("Match found! ({} > {})".format(avg, args.min_matches))
-else:
- raise SystemExit(
- "ERROR: Not enough matches are found - {} < {}".format(
- avg,
- args.min_matches))