Implemented goal detection in colorpicker

This commit is contained in:
2018-06-10 21:04:20 +02:00
parent caf88ab7e7
commit abc69fb69a
4 changed files with 98 additions and 11 deletions

View File

@@ -3,10 +3,12 @@ from __future__ import division
import json
import argparse
import cv2
import numpy as np
from .imagereaders import VideoReader, NaoImageReader, PictureReader
from .utils import read_config
from .utils import read_config, imresize
class Colorpicker(object):
@@ -19,7 +21,7 @@ class Colorpicker(object):
checkers = [
lambda x: min(x, self.settings['high_h'] - 1), # LOW H
lambda x: min(x, self.settings['high_s'] - 1), # LOW S
lambda x: min(x, self.settings['high_v'] - 1), # LOW H
lambda x: min(x, self.settings['high_v'] - 1), # LOW V
lambda x: max(x, self.settings['low_h'] + 1), # HIGH H
lambda x: max(x, self.settings['low_s'] + 1), # HIGH S
lambda x: max(x, self.settings['low_v'] + 1), # HIGH V
@@ -52,17 +54,75 @@ class Colorpicker(object):
cv2.setTrackbarPos(name, self.WINDOW_DETECTION_NAME,
self.settings[name])
def show_frame(self, frame, width=None):
def goal_similarity(self, contour):
contour = contour.reshape((-1, 2))
left, right = contour[:,0].min(), contour[:,0].max()
top, bottom = contour[:,1].min(), contour[:,1].max()
approx_line = np.array([
[left, bottom],
[left, top],
[right, top],
[right, bottom]
])
shape_sim = np.array([
(np.abs(contour - al)).sum(axis=1) for al in approx_line
])
len_a = cv2.arcLength(approx_line, False)
shape_sim = shape_sim.min(axis=1) / len_a
shape_sim = shape_sim.sum()
# len_c = cv2.arcLength(contour, True)
area_c = cv2.contourArea(contour)
# len_similarity = ((len_c / 2 - len_a) / len_a)**2
area_sim = area_c / ((right - left) * (bottom - top))
print(shape_sim, area_sim)
return shape_sim * area_sim
def draw_contours(self, thr):
thr = cv2.erode(thr, None, iterations=2)
thr = cv2.dilate(thr, None, iterations=2)
cnts, hier = cv2.findContours(thr.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
areas = np.array([cv2.contourArea(cnt) for cnt in cnts])
perimeters = np.array([cv2.arcLength(cnt, True) for cnt in cnts])
epsilon = 0.04 * perimeters
top_x = 6
if len(areas) > top_x:
cnt_ind = np.argpartition(areas, -top_x)[-top_x:]
cnts = [cnts[i] for i in cnt_ind]
perimeters = np.array([cv2.arcLength(cnt, True) for cnt in cnts])
epsilon = 0.005 * perimeters
cnts = [cv2.approxPolyDP(cnt, eps, True)
for cnt, eps in zip(cnts, epsilon)]
good_cnt = [cnt for cnt in cnts if 6 <= cnt.shape[0] <= 9
and not cv2.isContourConvex(cnt)]
if good_cnt:
good_cnt = [min(good_cnt, key=self.goal_similarity)]
# print(good_cnt[0])
thr = cv2.cvtColor(thr, cv2.COLOR_GRAY2BGR)
cv2.drawContours(thr, good_cnt, -1, (0, 255, 0), 2)
return thr
def show_frame(self, frame, width=None, draw_contours=False):
frame_HSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
frame_threshold = cv2.inRange(
frame_HSV,
tuple(map(self.settings.get, ('low_h', 'low_s', 'low_v'))),
tuple(map(self.settings.get, ('high_h', 'high_s', 'high_v')))
)
if width:
sf = width / frame.shape[1]
frame = cv2.resize(frame, (0, 0), fx=sf, fy=sf)
frame_threshold = cv2.resize(frame_threshold, (0, 0), fx=sf, fy=sf)
frame = imresize(frame, width=width)
frame_threshold = imresize(frame_threshold, width=width)
if draw_contours:
frame_threshold = self.draw_contours(frame_threshold)
cv2.imshow(self.WINDOW_CAPTURE_NAME, frame)
cv2.imshow(self.WINDOW_DETECTION_NAME, frame_threshold)
return cv2.waitKey(1)
@@ -71,7 +131,7 @@ class Colorpicker(object):
try:
with open(filename) as f:
conf = json.load(f)
except FileNotFoundError:
except IOError:
conf = {}
conf.update(self.settings)
with open(filename, 'w') as f:
@@ -166,7 +226,7 @@ if __name__ == '__main__':
while True:
if not args.still:
frame = rdr.get_frame()
key = cp.show_frame(frame, args.width)
key = cp.show_frame(frame, width=args.width, draw_contours=True)
if key == ord('q') or key == 27:
break
finally:

8
pykick/goal_hsv.json Normal file
View File

@@ -0,0 +1,8 @@
{
"low_s": 0,
"low_v": 159,
"high_h": 180,
"high_v": 255,
"low_h": 0,
"high_s": 62
}

View File

@@ -62,9 +62,10 @@ class VideoReader(object):
if not succ:
raise ValueError('Error while reading video')
self.ctr += 1
if self.ctr == self.cap.get(cv2.CAP_PROP_FRAME_COUNT) and self.loop:
if (self.ctr == self.cap.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT) and
self.loop):
self.ctr = 0
self.cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
self.cap.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, 0)
return frame
def close(self):

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@@ -1,5 +1,8 @@
from __future__ import division
import os
import json
from cv2 import resize as cv2_resize
HERE = os.path.dirname(os.path.realpath(__file__))
@@ -9,3 +12,18 @@ def read_config(cfg_file=os.path.join(HERE, 'nao_defaults.json')):
with open(cfg_file) as f:
cfg = json.load(f)
return cfg
def imresize(frame, width=None, height=None):
if not width and not height:
return frame
if not height:
sf = width / frame.shape[1]
sz = (0, 0)
if not width:
sf = height / frame.shape[0]
sz = (0, 0)
if width and height:
sf = 0
sz = (width, height)
return cv2_resize(frame, sz, fx=sf, fy=sf)