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