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sustaining_gazes_tnc
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Some changes

This commit is contained in:
Ruben van de Ven 2019-02-06 09:29:04 +01:00
parent 215a059a32
commit df6f7ce8db
1 changed files with 80 additions and 64 deletions
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144
head_pose.py
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@ -471,92 +471,108 @@ p.daemon = True
p.start() p.start()
processes.append(p) processes.append(p)
newMetrics = np.zeros((metricsSize[1], metricsSize[0]))
lastRunTime = 0
while True: while True:
te1 = time.time() result = None
result = pointsQueue.get() try:
te1b = time.time() te1 = time.time()
im = result['im'] result = pointsQueue.get()
currentPoint = result['currentPoint'] te1b = time.time()
currentPoints = result['currentPoints'] im = result['im']
currentPoint = result['currentPoint']
currentPoints = result['currentPoints']
except queue.Empty as e:
logger.warn('Result queue empty')
if not args.hide_preview: if result is not None:
# draw little floorplan for 10 -> 50, sideplan 60 -> 100 (40x40 px)
cv2.rectangle(im, (9, 9), (51, 51), (255,255,255), 1)
cv2.rectangle(im, (59, 9), (101, 51), (255,255,255), 1)
cv2.line(im, (10,10), (10,50), (200,200,200), 2)
cv2.line(im, (60,10), (60,50), (200,200,200), 2)
# screen is 16:10
cv2.rectangle(im, (9, 59), (91, 111), (255,255,255), 1)
if transform is None:
if not args.hide_preview: if not args.hide_preview:
cv2.putText(im, "1", (10,70), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['tl'] is not None else (0,0,255)) # draw little floorplan for 10 -> 50, sideplan 60 -> 100 (40x40 px)
cv2.putText(im, "2", (85,70), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['tr'] is not None else (0,0,255)) cv2.rectangle(im, (9, 9), (51, 51), (255,255,255), 1)
cv2.putText(im, "3", (10,110), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['bl'] is not None else (0,0,255)) cv2.rectangle(im, (59, 9), (101, 51), (255,255,255), 1)
cv2.putText(im, "4", (85,110), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['br'] is not None else (0,0,255)) cv2.line(im, (10,10), (10,50), (200,200,200), 2)
tm1 = 0 cv2.line(im, (60,10), (60,50), (200,200,200), 2)
tm2 = 0
tm3 = 0 # screen is 16:10
tm4 = 0 cv2.rectangle(im, (9, 59), (91, 111), (255,255,255), 1)
else:
tm1 = time.time() if transform is None:
newMetrics = np.zeros((metricsSize[1], metricsSize[0]))
tm2 = time.time()
for point in currentPoints:
# check if within coordinates:
# dot1 = np.dot(coordinates['tl'] - point, coordinates['tl'] - coordinates['br'])
# dot2 = np.dot(coordinates['bl'] - point, coordinates['tl'] - coordinates['br'])
# pointIn3 = [point[0], point[1], 0]
# targetPoint = np.dot(pointIn3, transformationMatrix)
# logger.info("Looking at", pointIn3, np.dot( transformationMatrix, pointIn3))
targetPoint = transform(point)
logger.info("Looking at {} {}".format(point, targetPoint) )
# cv2.circle(im, (int(targetPoint[0]), int(targetPoint[1])), 2, (0,255,0), -1)
# from 1920x1080 to 80x50
if not args.hide_preview: if not args.hide_preview:
miniTargetPoint = (int(targetPoint[0] / 1920 * 80 + 10), int(targetPoint[1] / 1080 * 50 + 60)) cv2.putText(im, "1", (10,70), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['tl'] is not None else (0,0,255))
cv2.circle(im, miniTargetPoint, 2, (0,255,0), -1) cv2.putText(im, "2", (85,70), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['tr'] is not None else (0,0,255))
targetInt = (int(targetPoint[0]), int(targetPoint[1])) cv2.putText(im, "3", (10,110), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['bl'] is not None else (0,0,255))
# check if point fits on screen: cv2.putText(im, "4", (85,110), cv2.FONT_HERSHEY_PLAIN, .7, (255,255,255) if coordinates['br'] is not None else (0,0,255))
# if so, measure it tm1 = 0
if targetInt[0]+spotSize[0] >= 0 and targetInt[1]+spotSize[1] >= 0 and targetInt[0]-spotSize[0] < metricsSize[0] and targetInt[1]-spotSize[0] < metricsSize[1]: tm2 = 0
dataframe = dataframe.append({'x':targetInt[0],'y':targetInt[1]}, ignore_index=True) tm3 = 0
logger.info("Put metric {},{} in metrix of {},{}".format(targetInt[1],targetInt[0], metricsSize[1], metricsSize[0])) tm4 = 0
for sx in range(spotSize[0]): else:
for sy in range(spotSize[1]): for point in currentPoints:
mx = targetInt[0] + sx - (spotSize[0]-1)/2 # check if within coordinates:
my = targetInt[1] + sy - (spotSize[1]-1)/2 # dot1 = np.dot(coordinates['tl'] - point, coordinates['tl'] - coordinates['br'])
# dot2 = np.dot(coordinates['bl'] - point, coordinates['tl'] - coordinates['br'])
# pointIn3 = [point[0], point[1], 0]
# targetPoint = np.dot(pointIn3, transformationMatrix)
# logger.info("Looking at", pointIn3, np.dot( transformationMatrix, pointIn3))
targetPoint = transform(point)
logger.info("Looking at {} {}".format(point, targetPoint) )
# cv2.circle(im, (int(targetPoint[0]), int(targetPoint[1])), 2, (0,255,0), -1)
# from 1920x1080 to 80x50
if not args.hide_preview:
miniTargetPoint = (int(targetPoint[0] / 1920 * 80 + 10), int(targetPoint[1] / 1080 * 50 + 60))
cv2.circle(im, miniTargetPoint, 2, (0,255,0), -1)
targetInt = (int(targetPoint[0]), int(targetPoint[1]))
# check if point fits on screen:
# if so, measure it
if targetInt[0]+spotSize[0] >= 0 and targetInt[1]+spotSize[1] >= 0 and targetInt[0]-spotSize[0] < metricsSize[0] and targetInt[1]-spotSize[0] < metricsSize[1]:
dataframe = dataframe.append({'x':targetInt[0],'y':targetInt[1]}, ignore_index=True)
logger.info("Put metric {},{} in metrix of {},{}".format(targetInt[1],targetInt[0], metricsSize[1], metricsSize[0]))
for sx in range(spotSize[0]):
for sy in range(spotSize[1]):
mx = targetInt[0] + sx - (spotSize[0]-1)/2
my = targetInt[1] + sy - (spotSize[1]-1)/2
if mx >= 0 and my >= 0 and mx < metricsSize[0] and my < metricsSize[1]: if mx >= 0 and my >= 0 and mx < metricsSize[0] and my < metricsSize[1]:
newMetrics[my,mx] += spot[sx,sy] #/ 20 newMetrics[my,mx] += spot[sx,sy] #/ 20
# print("MAX",np.max(newMetrics)) # print("MAX",np.max(newMetrics))
# TODO: put in an image of a blurred spot & remove blur action # TODO: put in an image of a blurred spot & remove blur action
# after we collected all new metrics, blur them foor smoothness # after we collected all new metrics, blur them foor smoothness
# and add to all metrics collected # and add to all metrics collected
tm3 = time.time() tm3 = time.time()
# metrics = metrics + gaussian_filter(newMetrics, sigma = 13) # metrics = metrics + gaussian_filter(newMetrics, sigma = 13)
metrics = metrics + newMetrics
tm4 = time.time() tm4 = time.time()
logger.debug("Updated matrix with blur in %f", tm4 - tm3 + tm2 - tm1) # logger.debug("Updated matrix with blur in %f", tm4 - tm3 + tm2 - tm1)
# Display webcam image with overlays # Display webcam image with overlays
te2 = time.time() te2 = time.time()
if not args.hide_preview: if result is not None and not args.hide_preview:
cv2.imshow("Output", im) cv2.imshow("Output", im)
te3 = time.time() te3 = time.time()
logger.debug("showed webcam image in %fs", te3-te2) logger.debug("showed webcam image in %fs", te3-te2)
logger.debug("Rendering took %fs", te3-te1) logger.debug("Rendering took %fs", te3-te1)
logger.debug("Waited took %fs", te1b-te1) logger.debug("Waited took %fs", te1b-te1)
# blur smooth the heatmap # blur smooth the heatmap
# logger.debug("Max blurred metrics: %f", np.max(metrics)) # logger.debug("Max blurred metrics: %f", np.max(metrics))
# update the heatmap output # update the heatmap output
tm21 = time.time() tm21 = time.time()
t = tm21
diffT = min(1, t - lastRunTime)
# animDuration = 1
# factor = animDuration
metrics = metrics + newMetrics*diffT
newMetrics *= (1-diffT)
# smooth impact of first hits by having at least 0.05 # smooth impact of first hits by having at least 0.05
normalisedMetrics = metrics / (max(255*7 ,np.max(metrics))) normalisedMetrics = metrics / (max(255*7 ,np.max(metrics)))
# convert to colormap, thanks to: https://stackoverflow.com/a/10967471 # convert to colormap, thanks to: https://stackoverflow.com/a/10967471