def slideshow(self):
for imgName in glob.glob("/beta/Work/2/postbake/*.png", recursive=True):
img = cv2.imread(imgName)
# img = cv2.resize(img, dsize=None, fx=0.7, fy=0.7)
img = img[:, 100:-300]
# img = cv2.resize(img, (800, 800))
# out = []
out = self.P.predict(img, threshold=0.07)
for i, x in enumerate(out):
cid = x[0]
score = x[1]
roi = x[2:]
label = '|{}|.{:.3f}'.format(cid, score)
ImgUtils.drawRect(roi, img, colour=(255, 0, 0))
cv2.putText(img=img, text=label, org=(int(roi[0]), int(roi[1])),
fontFace=cv2.FONT_HERSHEY_PLAIN, thickness=1, lineType=cv2.LINE_4,
fontScale=2, color=(0, 255, 255))
print('\n')
while True:
ImgUtils.show("Feed", img, 0, 0)
key = cv2.waitKey(30)
if key == ord('q'):
return
elif key == ord('v'):
break
def raw1(self, img):
self.counter += 1
hBefore, wBefore, _ = img.shape
img = self.transformer.resize(img, 0, 270, 40, 500)
contrast = self.transform(img)
rois = DetectionUtils.detectContours(contrast,
widthLower=self.dim1Lower,
widthUpper=self.dim1Upper,
heightLower=self.dim2Lower,
heigthUpper=self.dim2Upper)
tracked, _ = self.tracker.track(rois)
self.numObjects = self.tracker.N
if self.guiMode:
for roi in rois:
ImgUtils.drawRect(roi, img)
detectedCentroid = ImgUtils.findRoiCentroid(roi)
ImgUtils.drawCircle(detectedCentroid, img, colour=(255, 0, 0))
for objectId, centroid in tracked.items():
ImgUtils.drawCircle((centroid[0], centroid[1]), img)
ImgUtils.putText(coords=centroid,
text=str(objectId % 1000),
img=img,
colour=(255, 0, 0))
return img, contrast, []
def showFeed(self):
while True:
_, feed = self.camera.read()
if feed is None:
continue
# self.frame = ImageTransforms.prepareResized(self.liveFeed)
# contrast = ImageTransforms.prepareMono(self.liveFeed)
ImgUtils.show("1", feed, 0, 0)
keyboard = cv2.waitKey(30)
if keyboard == 'q' or keyboard == 27:
break
def houghDetect(img, radiusMin, radiusMax):
"""
:param img: grayscale image with some circles
:return:[bounding rectangles]
"""
circles = cv2.HoughCircles(img,
cv2.HOUGH_GRADIENT,
1,
150,
param1=101,
param2=11,
minRadius=radiusMin,
maxRadius=radiusMax)
rois = []
radii = []
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
center = (i[0], i[1])
cv2.circle(img, center, 1, (0, 100, 100), 3)
radius = i[2]
if radiusMin < radius < radiusMax:
cv2.circle(img, center, radius, (255, 0, 255), 3)
roi = ImgUtils.findBoxAroundCircle(center, radius)
rois.append(roi)
radii.append(radius)
return rois, radii
def test(self):
while True:
_, feed = self.camera.read()
if feed is None:
continue
frame = StandardDetectionTrans.prepareMono(feed)
for i in range(3):
ImgUtils.show(str(i), frame[:, :, i], 0, 300 * i)
# ImgUtils.show('sum', cv2.bitwise_or(frame[:, :, 0], frame[:, :, 1]), 0, 800)
ImgUtils.show('Feed', StandardDetectionTrans.prepareResized(feed),
800, 0)
keyboard = cv2.waitKey(30)
if keyboard == 'q' or keyboard == 27:
break
def brick0(self, img):
# img = img[550:, 350:-400, :]
img = img[100:, :, :]
contrast = np.copy(img)
contrast = self.transform(contrast)
contours, h = cv2.findContours(contrast, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
rois = []
for c in contours:
approx = cv2.approxPolyDP(c, 0.01 * cv2.arcLength(c, True), True)
x, y, w, h = cv2.boundingRect(c)
if len(approx) < 1 or w < 130 or h < 60:
continue
x1 = x
x2 = x1 + w
y1 = y
y2 = y1 + h
if y1 < 250 or x2 < 100:
continue
rois.append([x1, y1, x2, y2])
# targetHeight = 130
# numParts = h // targetHeight
# if numParts < 1:
# rois.append([x1, y1, x2, y2])
# else:
# step = (h % targetHeight)
# y = y1
# for i in range(0, numParts):
# r = [x1, y, x2, y + targetHeight + step]
# y += (step + targetHeight)
# rois.append(r)
tracked, _ = self.tracker.track(rois)
self.numObjects = self.tracker.N
if self.guiMode:
for roi in rois:
ImgUtils.drawRect(roi, img)
detectedCentroid = ImgUtils.findRoiCentroid(roi)
ImgUtils.drawCircle(detectedCentroid, img, colour=(255, 0, 0))
for objectId, centroid in tracked.items():
ImgUtils.drawCircle((centroid[0], centroid[1]), img)
ImgUtils.putText(coords=centroid,
text=str(objectId % 1000),
img=img,
colour=(255, 0, 0))
return img, contrast, []
def main(self, draw=False):
clock = 0
while True:
clock += 1
_, self.liveFeed = self.camera.read()
if self.liveFeed is None:
continue
self.frame = StandardDetectionTrans.prepareResized(self.liveFeed)
# detect
contrast = StandardDetectionTrans.prepareMono(self.liveFeed)
rois = self.D.detect(contrast)
if draw:
for roi in rois:
ImgUtils.drawRect(roi, self.frame, colour=(0, 255, 255))
# track
self.T.track(rois)
print('--', self.T.N)
###
ImgUtils.show("Live", self.frame, 800, 0)
ImgUtils.show("Frame", contrast, 0, 0)
keyboard = cv2.waitKey(30)
if keyboard == 'q' or keyboard == 27:
break
def test(self):
for imgName in glob.glob("/beta/Work/2/postbake/*.png",
recursive=True):
# for imgName in glob.glob("/beta/Work/2/Train/1/*.png", recursive=True):
img = cv2.imread(imgName)
# img = cv2.resize(img, dsize=None, fx=0.7, fy=0.7)
img = img[50:-50, 500:850]
# img = cv2.resize(img, (300, 300))
# out = []
out = self.P.predict(img, threshold=0.7)
for i, x in enumerate(out):
print(x)
cid = x[0]
score = x[1]
roi = x[2]
centre = ImgUtils.findRoiCentroid(roi)
cv2.circle(img, centre, 20, (255, 0, 255), 3)
label = '|{}|.{:.3f}'.format(cid, score)
ImgUtils.drawRect(roi, img, colour=(255, 0, 0))
cv2.putText(img=img,
text=label,
org=(int(roi[0]), int(roi[1])),
fontFace=cv2.FONT_HERSHEY_PLAIN,
thickness=1,
lineType=cv2.LINE_4,
fontScale=2,
color=(0, 255, 255))
while True:
ImgUtils.show("Feed", img, 0, 0)
key = cv2.waitKey(30)
if key == ord('q'):
return
elif key == ord('v'):
break
def extractAndCopy(self, srcDirPath, extractor=0):
counter = 0
for i in range(10000):
imgPath = srcDirPath + str(i) + '.png'
# print(imgPath)
img = cv2.imread(imgPath)
if img is None:
continue
dets = self.extactors[str(extractor)].detectDebug(img)
# print(len(dets))
for det in dets:
ImgUtils.drawRect(det, img)
try:
counter += 1
except:
print("out of bounds")
if True:
ImgUtils.show('Img', img, 0, 0)
key = cv2.waitKey(30)
if key == ord('v'):
break
elif key == ord('q'):
return
return
counter = 0
filepathPrefix = "/beta/Work/2/Train/postbake/"
for imgName in glob.glob("/beta/Work/2/postbake/*.png",
recursive=True):
img = cv2.imread(imgName)
dets = self.D.detectDebug(img)
for (cX, cY), rad in dets:
if 600 < cX < 760 and 160 < cY < 560:
cv2.imwrite(
filepathPrefix + str(counter) + ".png",
ImgUtils.findCentroidVicinity(img, cX, cY, 300, 300))
counter += 1
while True:
ImgUtils.show('Img', img, 0, 0)
# if X is not None:
# ImgUtils.show('X', X, 800, 900)
key = cv2.waitKey(30)
if key == 27 or key == ord('v'):
break
elif key == ord('q'):
return
def desample(self, path, batchSize=3):
for i in range(0, 1000000, batchSize):
imgs = []
gmis = []
gims = []
for j in range(batchSize):
imgPath = path+str(i+j)+'.png'
img = cv2.imread(imgPath)
if img is None:
continue
img = img[60:240, 60:240, :]
imgs.append(img)
for j, img in enumerate(imgs):
# imgs[0] = ImgUtils.randomImage(red=(80, 240), blue=(10, 100), green=(80, 240), imgLike=img)
# imgs[1] = ImgUtils.randomImage(red=(0, 120), blue=(0, 120), green=(0, 120), imgLike=img)
# imgs[2] = ImgUtils.randomImage(red=(0, 255), blue=(0, 255), green=(0, 255), imgLike=img)
# imgs[3] = ImgUtils.randomImage(red=(120, 255), blue=(120, 255), green=(120, 255), imgLike=img)
# imgs[4] = ImgUtils.randomImage(red=(150, 170), blue=(30, 50), green=(30, 50), imgLike=img)
gmi = self.transform(imgs[j])
gmis.append(gmi)
ImgUtils.putText(img, str(np.mean(img[:, :, 2])), (10, 50), colour=(200, 0, 255))
img = ImgUtils.hconcat(imgs, pad=50)
gmi = ImgUtils.hconcat(gmis, pad=50)
# Y = ImgUtils.hconcat(imgs, channel=1)
# gmi[i, j] = (np.random.randint(10, 100), np.random.randint(70, 100), np.random.randint(80, 240))
while True:
ImgUtils.show('Img', img, 0, 0)
ImgUtils.show('Gmi', gmi, 0, 260)
# ImgUtils.show('Y', Y, 0, 720)
key = cv2.waitKey(500)
if key == ord('v'):
break
elif key == ord('q'):
return
def postbake1Debug(self, feed):
radiusMin = self.dim1Lower
radiusMax = self.dim1Upper
img = self.transform(feed)
circles = cv2.HoughCircles(img,
cv2.HOUGH_GRADIENT,
1,
150,
param1=101,
param2=11,
minRadius=radiusMin,
maxRadius=radiusMax)
dets = []
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
center = (i[0], i[1])
cv2.circle(img, center, 1, (0, 100, 100), 3)
radius = i[2]
if radiusMin < radius < radiusMax:
cv2.circle(img, center, radius, (255, 0, 255), 3)
dets.append(ImgUtils.findBoxAroundCircle(center, radius))
return dets
from detect import Detector
from imgUtils import ImgUtils
if __name__ == "__main__":
param = {
(1, 'postbake'): {
'expectedWidth': 120,
'expectedHeight': 110, # detection params
'transformationTarget':
'cool', # select correct image transformations
'upperKillzone': 550,
'lowerKillzone': 220, # select correct tracking parameters
'rightKillzone': 3000,
'leftKillzone': -3000, # select correct tracking parameters
'timeToDie': 1,
'timeToLive': 0,
'partioningRequired': True
}
}
D = Detector(**param.get((1, 'postbake')))
for i in range(49, 100):
img = cv2.imread("PostBakeSamples/postbake" + str(i) + ".png")
x = D.getImgWithBoxes(img)
while True:
ImgUtils.show("x", x, 0, 0)
key = cv2.waitKey(30)
if key == ord('q'):
break
def postbake1(self, img):
hBefore, wBefore, _ = img.shape
img = self.transformer.resize(img)
origImg = np.copy(img)
contrast = self.transform(img)
rois, radii = DetectionUtils.houghDetect(contrast,
radiusMin=self.dim1Lower,
radiusMax=self.dim1Upper)
tracked, newRois = self.tracker.track(rois)
self.numObjects = self.tracker.N
if self.guiMode:
for roi in rois:
ImgUtils.drawRect(roi, img)
detectedCentroid = ImgUtils.findRoiCentroid(roi)
ImgUtils.drawCircle(detectedCentroid, img, colour=(255, 0, 0))
ImgUtils.putText(coords=(roi[0] + 50, roi[1] + 50),
text=str(roi[2] - roi[0]),
img=img,
colour=(255, 255, 0),
fontSize=3)
for objectId, centroid in tracked.items():
ImgUtils.drawCircle((centroid[0], centroid[1]), img)
ImgUtils.putText(coords=centroid,
text=str(objectId % 1000),
img=img,
colour=(255, 0, 0))
out = []
for roi in newRois:
colour = self.colour(origImg[roi[1]:roi[3], roi[0]:roi[2]])
self.averageColour[0] += colour[0]
self.averageColour[1] += colour[1]
self.averageColour[2] += colour[2]
self.averageSize += roi[3] - roi[1]
return img, contrast, out