EValuate the generated images of GANS using FID and SSIM (MATLAB:2023a)
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I have generated an images using CGANS ( conditional Gans) as in the matlab official example:
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)
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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
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Ayush Aniket
2023-8-21
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
Shreeya
2023-8-29
编辑:Shreeya
2023-8-29
Hi @MAHMOUD EID
Find the implementation of the wassersteinDistance below
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.
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