Giter Site home page Giter Site logo

furkanu / deeplearning.ai-pytorch Goto Github PK

View Code? Open in Web Editor NEW
149.0 149.0 33.0 68.31 MB

PyTorch Implementations of Coursera's Deep Learning(deeplearning.ai) Specialization

License: MIT License

Jupyter Notebook 97.27% Python 2.73%
coursera-deep-learning coursera-specialization deep-learning pytorch

deeplearning.ai-pytorch's People

Contributors

furkanu avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

deeplearning.ai-pytorch's Issues

Bug In "Art Generation with Neural Style Transfer"

Hi, I learn a lot from your code! Thanks a lot!

I think there is a bug in the save_image function of Art Generation with Neural Style Transfer code. Since .detach() share the same memory, we should clone the input image first or the change will apply to the original image and mess the training.

Bellow is the fixed code for save_image

def save_image(path, imageO):
    # Un-normalize the image so that it looks good
    image=imageO.clone().detach()
    image = image.cpu().numpy().transpose(0, 2, 3, 1)
    image += CONFIG.MEANS
    image = np.clip(image[0], 0, 255).astype('uint8')

pretrained weights for FaceNet and Emoji data?

Hi! I have cloned your repo and tried to run the files and encountered two missing file error: when I run the FaceNet code, I found the following error indicates that the weight is missing:

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
<ipython-input-13-6d45e7bac014> in <module>
      1 loss_fn = TripletLoss()
      2 optimizer = optim.Adam(FRmodel.parameters())
----> 3 load_weights_from_FaceNet(FRmodel)

~/Desktop/ml_ross/deeplearning.ai-pytorch/4- Convolutional Neural Networks/Week 4/Face Recognition (Done)/inception_model.py in load_weights_from_FaceNet(model)
    458 
    459 def load_weights_from_FaceNet(model):
--> 460     weights_dict = load_weights()
    461 
    462     state_dict = {}

~/Desktop/ml_ross/deeplearning.ai-pytorch/4- Convolutional Neural Networks/Week 4/Face Recognition (Done)/inception_model.py in load_weights()
    359     # Set weights path
    360     dirPath = './weights'
--> 361     fileNames = filter(lambda f: not f.startswith('.'), os.listdir(dirPath))
    362     paths = {}
    363     weights_dict = {}

FileNotFoundError: [Errno 2] No such file or directory: './weights'

When I run the Emojify code, I found that the emoji data file seems to be missing:

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
<ipython-input-2-8319399d5196> in <module>
----> 1 X_train, Y_train = read_csv('data/train_emoji.csv')
      2 X_test, Y_test = read_csv('data/tesss.csv')

~/Desktop/ml_ross/deeplearning.ai-pytorch/5- Sequence Models/Week 2/2- Emojify/emo_utils.py in read_csv(filename)
     35     emoji = []
     36 
---> 37     with open (filename) as csvDataFile:
     38         csvReader = csv.reader(csvDataFile)
     39 

FileNotFoundError: [Errno 2] No such file or directory: 'data/train_emoji.csv'

Do you mind also upload the facenet weights as well as the emoji data to your repo, or direct me to where I can download that? Thank you very much for the help!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.