cannot download vgg16_weights

TriLoo commented 7 years ago

Hi fchollet, Now, I'm using vgg16 under Keras to classify oxford 102 flower dataset and I want to download the trained weight file: vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5. But I cannot download it... Wourld you please email this file to me? thank u very much. my email: songmh_1@hotmail.com

gugarosa commented 7 years ago

Just use this straight link: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5

kashyap32 commented 7 years ago

You can download it manually from here: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5 and paste it on ~/.keras/models

muthiyanbhushan commented 7 years ago

Hello everyone,

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 model = VGG16(weights="imagenet") File "/home/nvidia/deep-learning-models/imagenet-example/vgg16.py", line 143, in VGG16 cache_subdir='models') File "build/bdist.linux-aarch64/egg/keras/utils/data_utils.py", line 222, in get_file Exception: URL fetch failure on https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5: None -- [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:590)

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.

srinivaschalamala commented 7 years ago

Export proxy environment variables http_proxy, socks_proxy, https_proxy,ftp_proxy etc

helxsz commented 7 years ago

I faced the same problem that the vgg16_weights_tf_dim_ordering_tf_kernels.h5 was downloaded directly from the browser and placed into the ./keras/models folder, but when the application is running, it is still downloading the model, why it is happening

sudhir2016 commented 6 years ago

I am facing the same issue. Even if I download and manually place the VGG16 weights file in Keras model folder the program still tries to downloads and stops after downloading about 33 MB with the error 'Connection closed by remote host'. Please suggest solution.

DianaLi96 commented 6 years ago

I also met the same problem.I download the weight file manually,but it also make me download repeatedly. How can I solve the problem.Thank you!

sai-sundar commented 6 years ago

I faced the same problem found a work around like this ! If you are using VGG16 from keras.applications or from 'https://github.com/fchollet/deep-learning-models' the download happens in any case. Now in order to stop this download what I did was took the vgg16.py from the link I just mentioned and then provided the path where I stored my manually downloaded weights. This happens at line 170 in vgg16.py where you can comment the if/else condition and modify the load_weights accordingly. Finally include 'from vgg16 import VGG16' to your main python file. Hope this made sense.

eltronix commented 6 years ago

If you're on Mac OS, I found a solution here: https://github.com/ageron/handson-ml/issues/46

aarshee commented 6 years ago

If you download the model from https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5 make sure you set the include_top variable as False: model = VGG16(weights = 'imagenet', include_top = False)

ClaudeCoulombe commented 6 years ago

For Mac OS X

1) Update to Python 3.6.5 using the native app installer downloaded from the official Python language website https://www.python.org/downloads/

I've found that the installer is taking care of updating the links and symlinks for the new Python a lot better than homebrew.

2) Install a new certificate using "./Install Certificates.command" which is in the refreshed Python 3.6 directory

> cd "/Applications/Python 3.6/"
> sudo "./Install Certificates.command"

unnir commented 6 years ago

add these lines before downloading the weights:

import ssl

ssl._create_default_https_context = ssl._create_unverified_context

yzc1112 commented 6 years ago

Hi, guys, I found a really easy solution. If you cannot download it due to proxy settings in a company like me. You can use PyPAC to auto set proxy for you by using the internet explorer's setting

download PyPAC open your terminal and type pip install pypac
inside your python code, write the following: from keras.applications import resnet50 from pypac import pac_context_for_url import ssl context = ssl._create_unverified_context() with pac_context_for_url('https://www.google.com'): # put any website here, it just uses the website to get proxy settings model = resnet50.ResNet50() # put the download code line under your pac_context_for_url(''): function.

here you go

Red-Eyed commented 6 years ago

@unnir , thank you a lot, it works!!

drscarlat commented 6 years ago

@unnir - many thanx for your elegant solution !

MLEinmaking commented 5 years ago

Downloading https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5 and passing the path to weights worked for me. self.resnet = ResNet50(weights='models/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5', include_top=False, pooling='avg')

duocang commented 5 years ago

copy paste and run. you see my power.

from keras.applications import VGG16
from keras import backend as K
import tensorflow as tf

import httplib2
# detect presense of proxy and use env varibles if they exist
pi = httplib2.proxy_info_from_environment()
if pi:
    import socks
    socks.setdefaultproxy(pi.proxy_type, pi.proxy_host, pi.proxy_port)
    socks.wrapmodule(httplib2)    

# now all calls through httplib2 should use the proxy settings
httplib2.Http()

mn = VGG16()
saver = tf.train.Saver()
sess = K.get_session()
saver.save(sess, "./TF_Model/vgg16")

clived2 commented 5 years ago

I faced the same problem that the vgg16_weights_tf_dim_ordering_tf_kernels.h5 was downloaded directly from the browser and placed into the ./keras/models folder, but when the application is running, it is still downloading the model, why it is happening

I am having the same problem, please advise

Red-Eyed commented 5 years ago

What error message do u have?

clived2 commented 5 years ago

Hi

It just seemed to freeze when I was downloading the vgg16_weights, but it worked today and I completed the assignment

On Tue, May 28, 2019 at 1:33 AM Vadym Stupakov notifications@github.com wrote:

What error message do u have?

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