Hi
The image and webcam demos are working fine. However the run_video.py returns only background video without any skeletons being drawn. As the video finishes playing I get the following error:
Exception: The image is not valid. Please check your image exists.
Full error log attached.
error3.txt
Any help would be appreciated.
I managed to solve the issue myself by combining run_webcam.py and run_video.py. I must note that I do not have a programming background so I am not 100% sure why it works this way. It seems that resizing fixed the issue.
I run it with the following command (similar to webcam demo):
$ python run_video.py --model=mobilenet_thin --video=video.mp4 --resize=432x368
import argparse
import logging
import time
import cv2
import numpy as np
from estimator import TfPoseEstimator
from networks import get_graph_path, model_wh
logger = logging.getLogger('TfPoseEstimator-Video')
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
formatter = logging.Formatter('[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s')
ch.setFormatter(formatter)
logger.addHandler(ch)
fps_time = 0
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='tf-pose-estimation Video')
parser.add_argument('--video', type=str, default='')
parser.add_argument('--resize', type=str, default='0x0',
help='if provided, resize images before they are processed. default=0x0, Recommends : 432x368 or 656x368 or 1312x736 ')
parser.add_argument('--resize-out-ratio', type=float, default=4.0,
help='if provided, resize heatmaps before they are post-processed. default=1.0')
parser.add_argument('--model', type=str, default='mobilenet_thin', help='cmu / mobilenet_thin')
parser.add_argument('--show-process', type=bool, default=False,
help='for debug purpose, if enabled, speed for inference is dropped.')
parser.add_argument('--showBG', type=bool, default=True, help='False to show skeleton only.')
args = parser.parse_args()
logger.debug('initialization %s : %s' % (args.model, get_graph_path(args.model)))
w, h = model_wh(args.resize)
if w > 0 and h > 0:
e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))
else:
e = TfPoseEstimator(get_graph_path(args.model), target_size=(432, 368))
cap = cv2.VideoCapture(args.video)
if cap.isOpened() is False:
print("Error opening video stream or file")
while cap.isOpened():
ret_val, image = cap.read()
logger.debug('image process+')
humans = e.inference(image, resize_to_default=(w > 0 and h > 0), upsample_size=args.resize_out_ratio)
if not args.showBG:
image = np.zeros(image.shape)
logger.debug('postprocess+')
image = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)
logger.debug('show+')
cv2.putText(image, "FPS: %f" % (1.0 / (time.time() - fps_time)), (10, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.imshow('tf-pose-estimation result', image)
fps_time = time.time()
if cv2.waitKey(1) == 27:
break
cv2.destroyAllWindows()
logger.debug('finished+')
bingo
you are so coooooool
Thank you so much !!!
Hi, thanks for your work, when I run this code, I got below error:
from . import decays
File "/home/anaconda3/lib/python3.6/site-packages/estimator/decays.py", line 7, in
cosine = tf.train.cosine_decay
AttributeError: module 'tensorflow.python.training.training' has no attribute 'cosine_decay'
Maybe, do you know how to solve it? Thanks in advance.
Hi, thanks for your work, when I run this code, I got below error:
from . import decays
File "/home/anaconda3/lib/python3.6/site-packages/estimator/decays.py", line 7, in
cosine = tf.train.cosine_decay
AttributeError: module 'tensorflow.python.training.training' has no attribute 'cosine_decay'Maybe, do you know how to solve it? Thanks in advance.
Hello, I have encountered the same problem. Have you solved it
Thank you!!
Most helpful comment
I managed to solve the issue myself by combining run_webcam.py and run_video.py. I must note that I do not have a programming background so I am not 100% sure why it works this way. It seems that resizing fixed the issue.
I run it with the following command (similar to webcam demo):
$ python run_video.py --model=mobilenet_thin --video=video.mp4 --resize=432x368