(measure) C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src>python demo.py ctdet --demo webcam --load_model ../models/ctdet_coco_dla_2x.pth
Fix size testing.
training chunk_sizes: [32]
The output will be saved to C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib....\exp\ctdet\default
heads {'hm': 80, 'wh': 2, 'reg': 2}
Creating model...
Downloading: "http://dl.yf.io/dla/models\imagenet\dla34-ba72cf86.pth" to C:\Users\IFL/.cache\torch\checkpoints\dla34-ba72cf86.pth
Traceback (most recent call last):
File "demo.py", line 56, in
demo(opt)
File "demo.py", line 21, in demo
detector = Detector(opt)
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\detectors\ctdet.py", line 22, in init
super(CtdetDetector, self).init(opt)
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\detectors\base_detector.py", line 24, in init
self.model = create_model(opt.arch, opt.heads, opt.head_conv)
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\models\model.py", line 28, in create_model
model = get_model(num_layers=num_layers, heads=heads, head_conv=head_conv)
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\models\networks\pose_dla_dcn.py", line 491, in get_pose_net
head_conv=head_conv)
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\models\networks\pose_dla_dcn.py", line 434, in init
self.base = globals()base_name
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\models\networks\pose_dla_dcn.py", line 314, in dla34
model.load_pretrained_model(data='imagenet', name='dla34', hash='ba72cf86')
File "C:\Users\IFL\Desktop\Liu\Detector\CenterNet\src\lib\models\networks\pose_dla_dcn.py", line 300, in load_pretrained_model
model_weights = model_zoo.load_url(model_url)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\site-packages\torch\hub.py", line 433, in load_state_dict_from_url
_download_url_to_file(url, cached_file, hash_prefix, progress=progress)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\site-packages\torch\hub.py", line 349, in _download_url_to_file
u = urlopen(url)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 223, in urlopen
return opener.open(url, data, timeout)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 532, in open
response = meth(req, response)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 642, in http_response
'http', request, response, code, msg, hdrs)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 570, in error
return self._call_chain(*args)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 504, in _call_chain
result = func(*args)
File "C:\Users\IFL\Anaconda3\envs\measure\lib\urllib\request.py", line 650, in http_error_default
raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 404: Not Found
Can you tell me how can i fix it?
directly download the file from url save it to the target folder @Innan666
I got the same issue. I tried to get http://dl.yf.io/dla/models\imagenet\dla34-ba72cf86.pth but I got 404 error also. How can we fix it?
I got the same issue. I tried to get but I got 404 error also. How can we fix it?
I got it. Get into http://dl.yf.io/dla/models/imagenet and download dla34-ba72cf86.pth directly.
@Innan666 , @haryngod
in windows system has problem at that parts. so u should change that cord or download directly.
u can change that part like below;
url = 'http://dl.yf.io/dla/models/' + data + '/{}-{}.pth'.format(name, hash)
return url
I got the same issue. I tried to get but I got 404 error also. How can we fix it?
I got it. Get into http://dl.yf.io/dla/models/imagenet and download dla34-ba72cf86.pth directly.
Where do I put it when I download it
@Innan666 , @haryngod
in windows system has problem at that parts. so u should change that cord or download directly.
u can change that part like below;
url = 'http://dl.yf.io/dla/models/' + data + '/{}-{}.pth'.format(name, hash)
return url
Thank you for your help, where do I put it when I download directly
@howdidthatwork
I fixed the problem by downloading the pre-trained model on the link given by @haryngod then paste the pre-trained model in the checkpoint folder
