EValuate the generated images of GANS using FID and SSIM (MATLAB:2023a)

21 次查看（过去 30 天）
MAHMOUD EID
MAHMOUD EID 2023-8-3
评论： John 2024-2-21
I have generated an images using CGANS ( conditional Gans) as in the matlab official example:
https://se.mathworks.com/help/deeplearning/ug/train-conditional-generative-adversarial-network.html?searchHighlight=cgans&s_tid=srchtitle_support_results_1_cgans
Howerver, I need to write a code to evaluate the smilarity between the orignial images and generated images using FID (Frechet Inception Distance (FID) or Image Quality Measures (SSIM)
  1 个评论
Fatima Bibi
Fatima Bibi 2024-2-13
编辑：Fatima Bibi 2024-2-13
i also want this question answer i want to load cgan pretrained model that matches model images with original images
my original images have one folder that contain 5 classes.i want it matches randomly 10 images per class for FID

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Ayush Aniket
Ayush Aniket 2023-8-21
Hi MAHMOUD EID,
For calculating SSIM for the generated images you can use the MATLAB inbuilt ‘ssim’ function as follows:
% Load and preprocess the original and generated images
original_images = imread('path/to/original/image.jpg');
generated_images = imread('path/to/generated/image.jpg');
% Calculate Structural Similarity Index Measure (SSIM)
ssim_score = ssim(original_images, generated_images);
You can read more about the function in the documentation page: https://in.mathworks.com/help/images/ref/ssim.html
For calculating FID, you can use pre-trained Inception-v3 model from the Deep Learning Toolbox as follows:
net = inceptionv3;
% Calculate Frechet Inception Distance (FID)
original_features = activations(net, original_image, 'avg_pool');
generated_features = activations(net, generated_image, 'avg_pool');
fid_score = wassersteinDistance(original_features, generated_features);
You can read about the model here : https://in.mathworks.com/help/deeplearning/ref/inceptionv3.html
You may need the check for the size compatibility of your images and that required as input to the Inception-v3 model.
Hope this helps!
  3 个评论
显示 1更早的评论
John
John 2024-2-21
Is the 'original image' before the 'net'? For example, is it the 'noised image' before denoising? If that is the case, then "ssim(original_images, generated_images);" will not be much meaningful. I am not sure how about the Frechet Inception Distance (FID).
What kind of appropriate quantitative evaluation for, for example, unsupervised Cycle GAN generated denoised images? There are two group of images here: noisy-image and denoised-image; the training net is available.
Thank you.

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Image Segmentation and Analysis 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by