copilot/OpenSeeFace
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Changed visualization colors and added more options regarding video output.

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This commit is contained in:
Emiliana 2020-09-05 21:03:54 +02:00
parent 5bf3648b68
commit 28ed5e2f8e
1 changed files with 18 additions and 7 deletions
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25
facetracker.py
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@ -30,6 +30,8 @@ parser.add_argument("--discard-after", type=int, help="Set the how long the trac
parser.add_argument("--max-feature-updates", type=int, help="This is the number of seconds after which feature min/max/medium values will no longer be updated once a face has been detected.", default=900)
parser.add_argument("--no-3d-adapt", type=int, help="When set to 1, the 3D face model will not be adapted to increase the fit", default=1)
parser.add_argument("--video-out", help="Set this to the filename of an AVI file to save the tracking visualization as a video", default=None)
parser.add_argument("--video-scale", type=int, help="This is a resolution scale factor applied to the saved AVI file", default=1, choices=[1,2,3,4])
parser.add_argument("--video-fps", type=float, help="This sets the frame rate of the output AVI file", default=24)
parser.add_argument("--raw-rgb", type=int, help="When this is set, raw RGB frames of the size given with \"-W\" and \"-H\" are read from standard input instead of reading a video", default=0)
parser.add_argument("--log-data", help="You can set a filename to which tracking data will be logged here", default="")
parser.add_argument("--log-output", help="You can set a filename to console output will be logged here", default="")
@ -111,6 +113,7 @@ height = 0
width = 0
tracker = None
sock = None
total_tracking_time = 0.0
tracking_time = 0.0
tracking_frames = 0
frame_count = 0
@ -183,13 +186,15 @@ try:
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
tracker = Tracker(width, height, threshold=args.threshold, max_threads=args.max_threads, max_faces=args.faces, discard_after=args.discard_after, scan_every=args.scan_every, silent=False if args.silent == 0 else True, model_type=args.model, model_dir=args.model_dir, no_gaze=False if args.gaze_tracking != 0 else True, detection_threshold=args.detection_threshold, use_retinaface=args.scan_retinaface, max_feature_updates=args.max_feature_updates, static_model=True if args.no_3d_adapt == 1 else False)
if not args.video_out is None:
out = cv2.VideoWriter(args.video_out, cv2.VideoWriter_fourcc('F','F','V','1'), 24, (width,height))
out = cv2.VideoWriter(args.video_out, cv2.VideoWriter_fourcc('F','F','V','1'), args.video_fps, (width * args.video_scale, height * args.video_scale))
try:
inference_start = time.perf_counter()
faces = tracker.predict(frame)
if len(faces) > 0:
tracking_time += (time.perf_counter() - inference_start) / len(faces)
inference_time = (time.perf_counter() - inference_start)
total_tracking_time += inference_time
tracking_time += inference_time / len(faces)
tracking_frames += 1
packet = bytearray()
detected = False
@ -230,7 +235,7 @@ try:
if args.visualize > 1:
frame = cv2.putText(frame, str(f.id), (int(f.bbox[0]), int(f.bbox[1])), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (255,0,255))
if args.visualize > 2:
frame = cv2.putText(frame, f"{f.conf:.4f}", (int(f.bbox[0] + 18), int(f.bbox[1] - 6)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,255,0))
frame = cv2.putText(frame, f"{f.conf:.4f}", (int(f.bbox[0] + 18), int(f.bbox[1] - 6)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255))
for pt_num, (x,y,c) in enumerate(f.lms):
packet.extend(bytearray(struct.pack("f", y)))
packet.extend(bytearray(struct.pack("f", x)))
@ -245,7 +250,7 @@ try:
if args.visualize != 0 or not out is None:
if args.visualize > 3:
frame = cv2.putText(frame, str(pt_num), (int(y), int(x)), cv2.FONT_HERSHEY_SIMPLEX, 0.25, (255,255,0))
color = (0, 0, 255)
color = (0, 255, 0)
if pt_num >= 66:
color = (255, 255, 0)
if not (x < 0 or y < 0 or x >= height or y >= width):
@ -300,7 +305,12 @@ try:
sock.sendto(packet, (target_ip, target_port))
if not out is None:
out.write(frame)
video_frame = frame
if args.video_scale != 1:
video_frame = cv2.resize(frame, (width * args.video_scale, height * args.video_scale), interpolation=cv2.INTER_NEAREST)
out.write(video_frame)
if args.video_scale != 1:
del video_frame
if args.visualize != 0:
cv2.imshow('OpenSeeFace Visualization', frame)
@ -386,5 +396,6 @@ if not out is None:
cv2.destroyAllWindows()
if args.silent == 0 and tracking_frames > 0:
tracking_time = 1000 * tracking_time / tracking_frames
print(f"Average tracking time per detected face: {tracking_time:.2f} ms")
average_tracking_time = 1000 * tracking_time / tracking_frames
print(f"Average tracking time per detected face: {average_tracking_time:.2f} ms")
print(f"Tracking time: {total_tracking_time:.3f} s\nFrames: {tracking_frames}")