Autoencoders and GAN implementation - Python Implementation
Budget: ₹100 – ₹400 INR
Main Task - Image Reconstruction
1. Custom image Dataset must be loaded from the local drive. As of now you can load your own dataset.
2. Image Augmentation have to be included
Important: There should not be any restriction on the dimensions of the image. It will work with all the image dimensions
Step 1:
3. The various types of Autoencoder techniques and GAN must compared with and without hyper parameter tuning, Ensembling methods with various performance metrics.
4. There is an option to mention and control the types of noises with the range
5. The reconstructed results will be checked with the bunch of images or else the single image with similarity score with the input image.
1. Custom image Dataset must be loaded from the local drive. As of now you can load your own dataset.
2. Image Augmentation have to be included
Important: There should not be any restriction on the dimensions of the image. It will work with all the image dimensions
Step 1:
3. The various types of Autoencoder techniques and GAN must compared with and without hyper parameter tuning, Ensembling methods with various performance metrics.
4. There is an option to mention and control the types of noises with the range
5. The reconstructed results will be checked with the bunch of images or else the single image with similarity score with the input image.