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 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 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
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