Tree Image Classification using TF or Pytorch

[DARK-art108]

Task#1

• Implement Tree Image Classification using Tensorflow or Pytorch [No Barrier on Framework]
• Make use of Transfer Learning[Means use Pretrained Models like Resnet's, VGG, InceptionV3]
• Save the model in the format of model.bin or model.h5
• Apply different Data Augmentation techniques and resizing is important.

Dataset [Scrap By Yourself]

The dataset contains the images of Multiple categories of Tree-like Banana, Banyan, and others. Scrap the different tree images from google make sure you have scraped a maximum of 150 from each category.

• Make a global folder, which has other folders of different categories of trees, and make sure that the folders are in alphabetical order with starting with a lower case letter.

[Aditi0102]

Hello, I would like to contribute to this issue under GSSOC'21. Please assign me this issue.

[DARK-art108]

@Aditi0102 You can go ahead with the task, raise PR, and then I will take a look at it.

[Aditi0102]

Thank you :)

[Aditi0102]

Hello @DARK-art108, I've been working on this problem and have finished training my model, but at the time of upload, Git is unable to push a .h5 file to a remote repository. I've been trying it for a few days now and I've discovered that it's because of the large file size. And let me know what you think I should do.
Thank you so much

[DARK-art108]

@Aditi0102 zip the file drop in the Google drive with public access, and the model code file will be pushed to the repo, make sure you create a global folder and keep everything inside it and then push

[Aditi0102]

Hello @DARK-art108, I have sent a pull request regarding this issue, kindly review it.
Thank You

[saidrishya]

Hi, If the issue is still open, I would like to work on it. I am a GSSOC participant.