| import os | |
| import torch | |
| import PIL.Image as Image | |
| import matplotlib.pyplot as plt | |
| import sys | |
| sys.path.append("/home/ubuntu/Desktop/Domain_Adaptation_Project/repos/biastuning/") | |
| from utils import * | |
| results_folder_name = 'endovis18_10label_textaffine_decdertuning_4e-4_adamw_focal_alpha75e-2_gamma_2_256_bs64_rsz_manyaug_blanklables' | |
| ious_all = {} | |
| for object in os.listdir(results_folder_name): | |
| ious = [] | |
| print("Starting object: ", object) | |
| preds_path = os.path.join(results_folder_name, object, 'rescaled_preds') | |
| gt_path = os.path.join(results_folder_name, object, 'rescaled_gt') | |
| for i,im in enumerate(os.listdir(gt_path)): | |
| if i<13: | |
| continue | |
| label = np.array(Image.open(os.path.join(gt_path,im)))[60:306,150:400] | |
| label = (label>127)+0 | |
| pred = np.array(Image.open(os.path.join(preds_path,im)))[60:306, 150:400] | |
| pred = (pred>127) + 0 | |
| plt.imshow(label) | |
| plt.show() | |
| plt.imshow(label) | |
| plt.show() | |
| print(label.shape) | |
| print(pred.shape) | |
| print(np.unique(pred)) | |
| 1/0 |