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webcam_demo.py
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webcam_demo.py
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import tensorflow as tf
import cv2
import time
import argparse
from posenet.posenet_factory import load_model
from posenet.utils import draw_skel_and_kp
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=str, default='resnet50') # mobilenet resnet50
parser.add_argument('--stride', type=int, default=16) # 8, 16, 32 (max 16 for mobilenet)
parser.add_argument('--quant_bytes', type=int, default=4) # 4 = float
parser.add_argument('--multiplier', type=float, default=1.0) # only for mobilenet
parser.add_argument('--cam_id', type=int, default=0)
parser.add_argument('--cam_width', type=int, default=1280)
parser.add_argument('--cam_height', type=int, default=720)
parser.add_argument('--scale_factor', type=float, default=0.7125)
parser.add_argument('--file', type=str, default=None, help="Optionally use a video file instead of a live camera")
args = parser.parse_args()
def main():
print('Tensorflow version: %s' % tf.__version__)
assert tf.__version__.startswith('2.'), "Tensorflow version 2.x must be used!"
model = args.model # mobilenet resnet50
stride = args.stride # 8, 16, 32 (max 16 for mobilenet, min 16 for resnet50)
quant_bytes = args.quant_bytes # float
multiplier = args.multiplier # only for mobilenet
posenet = load_model(model, stride, quant_bytes, multiplier)
if args.file is not None:
cap = cv2.VideoCapture(args.file)
else:
cap = cv2.VideoCapture(args.cam_id)
cap.set(3, args.cam_width)
cap.set(4, args.cam_height)
start = time.time()
frame_count = 0
while True:
res, img = cap.read()
if not res:
raise IOError("webcam failure")
pose_scores, keypoint_scores, keypoint_coords = posenet.estimate_multiple_poses(img)
overlay_image = draw_skel_and_kp(
img, pose_scores, keypoint_scores, keypoint_coords,
min_pose_score=0.15, min_part_score=0.1)
cv2.imshow('posenet', overlay_image)
frame_count += 1
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print('Average FPS: ', frame_count / (time.time() - start))
if __name__ == "__main__":
main()