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from metrics import FID, LPIPS, Reconstruction_Metrics, preprocess_path_for_deform_task | |
import torch | |
device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu") | |
fid = FID() | |
lpips_obj = LPIPS() | |
rec = Reconstruction_Metrics() | |
real_path = './datasets/deepfashing/train_lst_512_png' | |
gt_path = '/datasets/deepfashing/test_lst_512_png' | |
distorated_path = './PCDMs_Results/stage3_512_results' | |
results_save_path = distorated_path + '_results.txt' # save path | |
gt_list, distorated_list = preprocess_path_for_deform_task(gt_path, distorated_path) | |
print(len(gt_list), len(distorated_list)) | |
FID = fid.calculate_from_disk(distorated_path, real_path, img_size=(352,512)) | |
LPIPS = lpips_obj.calculate_from_disk(distorated_list, gt_list, img_size=(352,512), sort=False) | |
REC = rec.calculate_from_disk(distorated_list, gt_list, distorated_path, img_size=(352,512), sort=False, debug=False) | |
print ("FID: "+str(FID)+"\nLPIPS: "+str(LPIPS)+"\nSSIM: "+str(REC)) | |
with open(results_save_path, 'a') as ff: | |
ff.write("\nFID: "+str(FID)+"\nLPIPS: "+str(LPIPS)+"\nSSIM: "+str(REC)) |