def gene_center_line(labels, data_list, rev_index, trace_list, debug=False):
n = len(labels)
x_list, y_list, angle_list = zip(*data_list)
pts_dict = defaultdict(list)
angle_dict = defaultdict(list)
rev_dict = defaultdict(list)
for i in range(n):
pts_dict[labels[i]].append([x_list[i], y_list[i]])
angle_dict[labels[i]].append(angle_list[i])
rev_dict[labels[i]].append(rev_index[i])
colors = ['pink', 'orange', 'y', 'blue', 'c', 'g', 'lime', 'red']
for label, pt_list in pts_dict.items():
rev = rev_dict[label]
if label == -2:
# draw_points(pt_list, '+', 'k', 0.1, -3)
pass
else:
if debug and label != 21:
continue
angle_list = angle_dict[label]
a = mean_angle(angle_list)
try:
# print a
idx = int(a / 45)
except ValueError:
continue
# print a
if len(pt_list) > 50:
a = 90 - a
line_list = collect_line_around(pt_list, trace_list, rev, a)
pt_list = rotate(pt_list, a)
org_list = rotate(pt_list, -a)
if debug:
draw_points(pt_list, 'o', colors[idx], .2, label)
# else:
# draw_points(pt_list, 'o', colors[idx], .1, label)
try:
print "label", label
road0, road1 = center_road(pt_list, line_list, debug)
road0 = road1
if not debug:
road0 = rotate(road0, -a)
draw_center(road0, 'k')
draw_line_idx(road0, label)
except ValueError:
print label, "ValueError"
except TypeError:
print label, "TypeError"
def collect_line_around(pt_list, trace_list, rev, rot):
"""
MOST important to road segment generation
trace_list[ti][tj] is pt
collect all the points from beginning to end as trace goes on if the point is anchor
because the vehicle may turn around and trace back, the trace should be split when turning happened
:param pt_list: list of anchor point
:param trace_list: original trace list, list of TaxiData
:param rev: each index
:param rot: rotate angle
:return: list of line(list of Point)
"""
# begin, end = {}, {}
trace_detail = {}
for i, pt in enumerate(pt_list):
ti, tj = rev[i][:]
try:
trace_detail[ti].append(tj)
except KeyError:
trace_detail[ti] = [tj]
for ti in trace_detail.keys():
trace_detail[ti].sort()
line_list = []
fact_ort = 90 - rot
for i, idx_list in trace_detail.items():
iset = set(idx_list)
for j in idx_list:
if j + 1 < len(trace_list[i]):
iset.add(j + 1)
fill_list = list(iset)
fill_list.sort()
line = []
last_j = None
for j in fill_list:
pt = trace_list[i][j]
if last_j is not None and j - last_j > 3:
if len(line) > 1:
line_list.append(rotate(line, rot))
line = [[pt.x, pt.y]]
else:
line.append([pt.x, pt.y])
last_j = j
if len(line) > 1:
line_list.append(rotate(line, rot))
return line_list
def run(self):
cap = cv2.VideoCapture(video)
out = cv2.VideoWriter(record, fourcc, cap.get(cv2.CAP_PROP_FPS),
(int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))), True)
while True:
ret, frame = cap.read()
if ret:
if fliplr_mark == -1:
frame = common.flipLeftToRight(frame)
if updown_mark == -1:
frame = common.upsidedown(frame)
if rotate_mark == -1:
frame = common.rotate(frame)
if RGBToWhite_mark == -1:
frame = common.RGBToWhite(frame)
if histogram_mark == -1:
frame = common.histogram_equalization_opti(frame)
frame = common.adjustS(frame, adjustS_mark)
print(adjustS_mark)
out.write(frame)
else:
break
window.pushButton_11.setText("Record/Save")
out.release()
def run(self):
cap = cv2.VideoCapture(video)
while True:
ret, frame = cap.read()
if ret:
if fliplr_mark == -1:
frame = common.flipLeftToRight(frame)
if updown_mark == -1:
frame = common.upsidedown(frame)
if rotate_mark == -1:
frame = common.rotate(frame)
if RGBToWhite_mark == -1:
frame = common.RGBToWhite(frame)
if histogram_mark == -1:
frame = common.histogram_equalization_opti(frame)
frame = common.adjustS(frame, adjustS_mark)
rgbImage = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
convertToQtFormat = QImage(rgbImage.data, rgbImage.shape[1],
rgbImage.shape[0],
QImage.Format_RGB888)
v = convertToQtFormat.scaled(640, 480, Qt.KeepAspectRatio)
if image_or_video == 1:
self.changePixmap.emit(v)
time.sleep(0.01)
else:
break
def run(self):
frame = cv2.imread(image)
if fliplr_mark == -1:
frame = common.flipLeftToRight(frame)
if updown_mark == -1:
frame = common.upsidedown(frame)
if rotate_mark == -1:
frame = common.rotate(frame)
if RGBToWhite_mark == -1:
frame = common.RGBToWhite(frame)
if histogram_mark == -1:
frame = common.histogram_equalization_opti(frame)
frame = common.adjustS(frame, adjustS_mark)
cv2.imwrite(image_save, frame)
window.pushButton_11.setText("Record/Save")
shapelyPoligons = []
for poligon in mark.poligons:
pol = Polygon(poligon)
shapelyPoligons.append(pol)
#Generating random poligons
refLocalPoligons = []
for i in range(negativeNum):
negAngle = random.random() * 90
negIndex = int(random.random() * len(refRects))
shift = (np.random.rand(2) * img.shape).astype(dtype=int)[::-1]
#rotate and transpose
negPoligon = refRects[negIndex].copy()
negPoligon = common.rotate(negPoligon, negAngle)
negPoligon = common.transpose(negPoligon, shift)
negPolygonShapely = Polygon(negPoligon)
#Check collision
noCollisions = True
if not imgPolygonShapely.contains(negPolygonShapely):
noCollisions = False
for shapelyPoligon in shapelyPoligons:
if shapelyPoligon.intersects(negPolygonShapely):
noCollisions = False
if masked and not common.checkMaskContains(mask, negPoligon):
noCollisions = False
outParser = markParser.MarkParser()
refRects, refP, refAngles = common.loadParams(paramsPath)
for mark in parser.marks:
refLocalPoligons = []
for poligon in mark.poligons:
longLine1, longLine2 = common.getLongLines(poligon)
angle = np.mean([common.getAngle(longLine1), common.getAngle(longLine2)])
qAngle = min(refAngles, key=lambda x:abs(x-angle))
meanCoord = poligon.mean(axis=0)
perim = common.perim(poligon)
rectIndex = refP.index( min(refP, key=lambda x:abs(x-perim)) )
refPoligon = refRects[rectIndex]
refPoligonTr = common.rotate(refPoligon, qAngle)
refPoligonTr = common.transpose(refPoligonTr, meanCoord)
refPoligonTrShapely = Polygon(refPoligonTr)
if not imgPolygonShapely.contains(refPoligonTrShapely):
continue
if masked and not common.checkMaskContains(mask, refPoligonTr):
continue
refLocalPoligons.append(refPoligonTr)
outParser.marks.append( markParser.Mark(mark.imageName, refLocalPoligons) )
outParser.save(outListPath)
classifier = cPickle.load(fid)
img = cv2.imread(imagePath, cv2.CV_LOAD_IMAGE_GRAYSCALE)
mask = cv2.imread(maskPath, cv2.CV_LOAD_IMAGE_GRAYSCALE)
refRects, refP, refAngles = common.loadParams(paramsPath)
outPoligon = [(0, 0), (img.shape[1], 0), (img.shape[1], img.shape[0]),
(0, img.shape[0])]
imgPolygonShapely = Polygon(outPoligon)
for rectIndex in range(len(refRects)):
rect = refRects[rectIndex]
for angleIndex in range(len(refAngles)):
angle = refAngles[angleIndex]
for x in range(0, img.shape[1] - 50, 8):
for y in range(0, img.shape[0] - 50, 8):
rotRect = common.rotate(rect, angle)
trRotRect = common.transpose(rotRect, np.asarray((x, y)))
if mask[y, x] != 255:
continue
polygonShapely = Polygon(trRotRect)
if not imgPolygonShapely.contains(polygonShapely):
continue
crop = common.extractCrop(img, trRotRect, size)
hist = hog.compute(crop)
#print hist
#print hist.shape
pred = classifier.predict(np.transpose(hist))
print pred