Example #1
0
                            # cv2.putText(vis_roi,
                            #     "%s (%s)" % (who, confidence),
                            #     (sx1 + 2, sy1 + 20 + 20 * i),
                            #     cv2.FONT_HERSHEY_PLAIN, 1.1, color)
                        winning_label = recog.get_overall_prediction(predictions)

                        #rect_color = recog.LABEL_COLORS[winning_label]
                        karlness_update = 1 if who == "Karl" else 0
                    else:
                        #rect_color = (0, 255, 255)
                        karlness_update = 1

                    karlness = KARLNESS_DECAY * karlness + (1 - KARLNESS_DECAY) * karlness_update
                    rect_color = (0, 255 * (1 - karlness), 255 * karlness)

                    draw_rects(vis_roi, subtargets, rect_color)

                    if not contains(next_targets, subtargets[0]):
                        fixed_rect = [max(0, x1-BUFFER)+sx1,max(0, y1-BUFFER)+sy1,max(0, x1-BUFFER)+sx2,max(0, y1-BUFFER)+sy2]

                        s_last, c_last = size_and_center(fixed_rect)

                        next_targets.append((
                            fixed_rect,
                            0,
                            VELOCITY_DECAY*velocity+(1-VELOCITY_DECAY)*np.array(diff(c_last, c)),
                            karlness
                        ))
                else:
                    # draw_rects(vis, [rect], (0,0,255))
                    if misses < MAX_MISSES:
Example #2
0
            subtargets = detect(roi_copy,
                                cascade_nested,
                                size=(max(30, s[0] - REFIND_BUFFER),
                                      max(30, s[1] - REFIND_BUFFER)))
            if len(subtargets) == 1:
                sx1, sy1, sx2, sy2 = subtargets[0]
                if not contains(next_targets, subtargets[0]):
                    next_targets.append(([
                        max(0, x1 - BUFFER) + sx1,
                        max(0, y1 - BUFFER) + sy1,
                        max(0, x1 - BUFFER) + sx2,
                        max(0, y1 - BUFFER) + sy2
                    ], 0, None))
                vis_roi = vis[max(0, y1 - BUFFER):min(width, y2 + BUFFER),
                              max(0, x1 - BUFFER):min(height, x2 + BUFFER)]
                draw_rects(vis_roi, subtargets, (0, 255, 0))
                cv.SaveImage("%s/roi/%s.pgm" % (output_dir, time.time()),
                             cv.fromarray(roi_copy, allowND=True))
                cv.SaveImage(
                    "%s/face/%s.pgm" % (output_dir, time.time()),
                    cv.fromarray(roi[sx1:sx2, sy1:sy2].copy(), allowND=True))
            else:
                # draw_rects(vis, [rect], (0,0,255))
                if misses < MAX_MISSES:
                    next_targets.append((rect, misses + 1, None))

        targets = next_targets
        if is_auto:
            targeter.update_targets(targets)
        # print "targets: ", len(targets)
Example #3
0
                            #     (sx1 + 2, sy1 + 20 + 20 * i),
                            #     cv2.FONT_HERSHEY_PLAIN, 1.1, color)
                        winning_label = recog.get_overall_prediction(
                            predictions)

                        #rect_color = recog.LABEL_COLORS[winning_label]
                        karlness_update = 1 if who == "Karl" else 0
                    else:
                        #rect_color = (0, 255, 255)
                        karlness_update = 1

                    karlness = KARLNESS_DECAY * karlness + (
                        1 - KARLNESS_DECAY) * karlness_update
                    rect_color = (0, 255 * (1 - karlness), 255 * karlness)

                    draw_rects(vis_roi, subtargets, rect_color)

                    if not contains(next_targets, subtargets[0]):
                        fixed_rect = [
                            max(0, x1 - BUFFER) + sx1,
                            max(0, y1 - BUFFER) + sy1,
                            max(0, x1 - BUFFER) + sx2,
                            max(0, y1 - BUFFER) + sy2
                        ]

                        s_last, c_last = size_and_center(fixed_rect)

                        next_targets.append(
                            (fixed_rect, 0, VELOCITY_DECAY * velocity +
                             (1 - VELOCITY_DECAY) * np.array(diff(c_last, c)),
                             karlness))
Example #4
0
            x1, y1, x2, y2 = rect
            with the_lock:
                roi = low_image[max(0, y1-BUFFER):min(width, y2+BUFFER), max(0, x1-BUFFER):min(height, x2+BUFFER)]

            # draw_rects(vis, [[max(0, x1-BUFFER), max(0, y1-BUFFER), min(height, x2+BUFFER), min(width, y2+BUFFER)]], (255,0,0))

            subt = clock()
            s, c = size_and_center(rect)
            roi_copy = roi.copy()
            subtargets = detect(roi_copy, cascade_nested, size=(max(30, s[0]-REFIND_BUFFER), max(30, s[1]-REFIND_BUFFER)))
            if len(subtargets) == 1:
                sx1, sy1, sx2, sy2 = subtargets[0]
                if not contains(next_targets, subtargets[0]):
                    next_targets.append(([max(0, x1-BUFFER)+sx1,max(0, y1-BUFFER)+sy1,max(0, x1-BUFFER)+sx2,max(0, y1-BUFFER)+sy2], 0, None))
                vis_roi = vis[max(0, y1-BUFFER):min(width, y2+BUFFER), max(0, x1-BUFFER):min(height, x2+BUFFER)]
                draw_rects(vis_roi, subtargets, (0, 255, 0))
                cv.SaveImage("%s/roi/%s.pgm" % (output_dir, time.time()), cv.fromarray(roi_copy, allowND=True))
                cv.SaveImage("%s/face/%s.pgm" % (output_dir, time.time()), cv.fromarray(roi[sx1:sx2, sy1:sy2].copy(), allowND=True))
            else:
                # draw_rects(vis, [rect], (0,0,255))
                if misses < MAX_MISSES:
                    next_targets.append((rect, misses+1, None))

        targets = next_targets
        if is_auto:
            targeter.update_targets(targets)
        # print "targets: ", len(targets)

        dt = clock() - t
        # with the_lock:
        #     print "time: ", dt*1000