Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Accuracy on ImageNet-LT #17

Open
pengzhiliang opened this issue Sep 21, 2020 · 4 comments
Open

Accuracy on ImageNet-LT #17

pengzhiliang opened this issue Sep 21, 2020 · 4 comments

Comments

@pengzhiliang
Copy link

Hello, thank u for the effective method and clean code!
I try to change your code to run on ImageNet-LT, but get a not so good result.
The config is as follow:

NAME: 'BBN.ImageNet.coslr.res50.90epoch'
OUTPUT_DIR: './output/bbn/ImageNet'
SHOW_STEP: 50
SAVE_STEP: 30
VALID_STEP: 1
INPUT_SIZE: (224, 224)
COLOR_SPACE: 'RGB'
CPU_MODE: False

DATASET:
  ROOT: 'Dataset/ILSVRC2012'
  DATASET: 'ImageNet'
  DATA_TYPE: 'JPEG'
  TRAIN_JSON: 'datasets/ImageNet_LT/ImageNet_LT_train.txt'
  VALID_JSON: 'datasets/ImageNet_LT/ImageNet_LT_val.txt'

BACKBONE:  
  TYPE: 'bbn_res50'

MODULE:
  TYPE: 'GAP'

LOSS:
  LOSS_TYPE: 'CrossEntropy'

CLASSIFIER:
  TYPE: 'FC'
  BIAS: True

TRAIN:
  BATCH_SIZE: 256
  MAX_EPOCH: 90
  NUM_WORKERS: 16
  COMBINER:
    TYPE: 'bbn_mix'
  TENSORBOARD:
    ENABLE: False
  SAMPLER:
    TYPE: 'default'
    DUAL_SAMPLER:
      ENABLE: True
      TYPE: 'reverse'
  OPTIMIZER:
    TYPE: 'SGD'
    BASE_LR: 0.1
    MOMENTUM: 0.9
    WEIGHT_DECAY: 5e-4
  LR_SCHEDULER:
     TYPE: 'cosine'
     COSINE_DECAY_END: 0
     WARM_EPOCH: 5
    
TRANSFORMS:
  TRAIN_TRANSFORMS: ("random_resized_crop", "random_horizontal_flip", "color_jitter")
  TEST_TRANSFORMS: ("shorter_resize_for_crop", "center_crop")

TEST:
  BATCH_SIZE: 128
  NUM_WORKERS: 16
  MODEL_FILE: '/home/BBN/models/BBN.ImageNet.res50.90epoch.best_model.pth'

But only get 46.26% on val set, the baseline is about 44%
Have you run BBN on ImageNet and get some results? Can u tell me.
Thank u very much! @ZhouBoyan

@Vanint
Copy link

Vanint commented May 31, 2021

I obtain similar results. Do you solve this problem?

@pengzhiliang
Copy link
Author

No, I give it up

@YoursEver
Copy link

@pengzhiliang
Excuse me. What is the GPU card you used?
My master student tried to run this code for our fish image dataset, but she encountered the out-of-memory problem.
(Resnet-50, 128*128, batchsize=8, on 1080Ti / 2080Ti)

@woshiwby
Copy link

@pengzhiliang Excuse me. What is the GPU card you used? My master student tried to run this code for our fish image dataset, but she encountered the out-of-memory problem. (Resnet-50, 128*128, batchsize=8, on 1080Ti / 2080Ti)

Excuse me, when I used our mushroom dataset, I encountered "NameError : name ' tun_latin' is not defined" problem. Could you tell me how to solve it?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants