deep-learning-models
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Create a ResNet50 model fails
Hi,
I have a problem when I try to create a ResNet50 model. I am getting the next error:
Note: My keras version is keras.version='1.1.0'
Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_th_dim_ordering_th_kernels_notop.h5
Exception Traceback (most recent call last)
/home/fhdiaze/.local/lib/python2.7/site-packages/keras/applications/resnet50.pyc in ResNet50(include_top, weights, input_tensor) 207 TH_WEIGHTS_PATH_NO_TOP, 208 cache_subdir='models', --> 209 md5_hash='f64f049c92468c9affcd44b0976cdafe') 210 model.load_weights(weights_path) 211 if K.backend() == 'tensorflow':
/home/fhdiaze/.local/lib/python2.7/site-packages/keras/utils/data_utils.pyc in get_file(fname, origin, untar, md5_hash, cache_subdir) 82 urlretrieve(origin, fpath, dl_progress) 83 except URLError as e: ---> 84 raise Exception(error_msg.format(origin, e.errno, e.reason)) 85 except HTTPError as e: 86 raise Exception(error_msg.format(origin, e.code, e.msg))
Exception: URL fetch failure on https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_th_dim_ordering_th_kernels_notop.h5: None -- [Errno 111] Connection refused
Thanks.
You can download it manually and place it in the ~/.keras/models
folder.
Hello,
I am using Jetson TX2 (flashed with Jetpack 3.0) for the tutorial "ImageNet classification with Python and Keras". I have installed all the dependencies. I tried running the script as mentioned in the tutorial. It gave me below error:
Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5
Traceback (most recent call last):
File "test_imagenet.py", line 40, in
I tried downloading file and placed it in ~/.keras/models folder. But still, I am getting the same error.
Can someone help me with this.
Thank you.
hello, I am a student,i have the same problem,can you tell me how you solved the problem
You can download it manually and place it in the
~/.keras/models
folder.
This worked for me.