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When I use RGB_ ResNet50_ SUN model, select ONLY_ RGB: TRUE, the evaluation.py report an error #30
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Hi! Thanks for your question! It's been some time since the creation of this code so I will try to do my best to recall. I have been checking the code and it might be true that even though you are just using the RGB network the code still needs the precomputed semantic segmentations. Actually, if you take a look at the forward method of the RGBBranch:
It still needs semantic segmentation as an argument although it is not used. Sorry for that inconvenience, unfortunately, I am currently unable to make code changes so you will need to download the data or change the code yourself. |
Thank you for your answer. I will use semantic-segmentation-pytorch to complete a scene recognition for any individual image |
Hello, I'm sorry to bother you again! What I want to inquire about is how to obtain the images in folders noisy_annotations and noisy_scores, and how do you convert the output results of semantic segmentation into this? |
in config_SUN397.yaml:
MODEL:
ARCH: ResNet-50
PATH: ./Data/Model Zoo/SUN397/
NAME: RGB_ResNet50_SUN
ONLY_RGB: TRUE
ONLY_SEM: FALSE
TRAINING:
PRINT_FREQ: 10
PRECOMPUTED_SEM: FALSE
BATCH_SIZE:
TRAIN: 100
TEST: 1
LR: 2.5e-4
LR_DECAY: 10
MOMENTUM: 0.9
OPTIMIZER: DFW
POLY_POWER: 0.9
WEIGHT_DECAY: 5.0e-4
AVERAGE_LOSS: 20
VALIDATION:
PRINT_FREQ: 10
BATCH_SIZE:
TRAIN: 100
TEST: 1
TEN_CROPS: TRUE
error:
FileNotFoundError: [Errno 2] No such file or directory: './Data/Datasets/SUN397/noisy_annotations_RGB/val/conference_room/sun_aatxlublfjchvvzu.png'
the model is selecting PRECOMPUTED_ SEM: FALSE , still required noise_ Annotations_ RGB and noise_ Annotations_Scores ?
Thank you very much for answering my question!
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