hahattpro / crowd_counting_framework (public) (License: Unspecified) (since 2020-12-23) (hash sha1)
backupfrom https://github.com/ttpro1995/crowd_counting_framework
Clone URLs: https://rocketgit.com/user/hahattpro/crowd_counting_framework ssh://rocketgit@ssh.rocketgit.com/user/hahattpro/crowd_counting_framework git://git.rocketgit.com/user/hahattpro/crowd_counting_framework
debug/a-1 develop feature/add_can_adcrowdnet feature/add_context_aware_network feature/attn_can_adcrowd_simple feature/cache_dataloader feature/compact_cnn feature/compare_with_original_count feature/dataloader_not_divide_8 feature/debug_viz feature/documentation feature/improve_density_gen feature/improve_loss_fn feature/loader_full_and_augment feature/refactor-dataflow feature/refactor_ccnn_basecode feature/save_best feature/simple_cometml feature/train_context_aware_network_on_shtA feature/train_dev_test_split hotfix/fix_visualize_data_loader master meow_exp server-training with_apex
List of commits:
Subject Hash Author Date (UTC)
log some more be343dcc3b65f15f30e395eac3ca8271c09d1634 Thai Thien 2020-05-21 17:43:04
cometml project name 57ca8f68cbb0b650da74f7117ee60bd25bf0d8d4 Thai Thien 2020-05-21 17:39:54
train 1acb89895774528dcec61fad2f2872f2613bff75 Thai Thien 2020-05-21 17:34:11
train e67e3fcb8b77db53f990f8582e43c053f69d6c09 Thai Thien 2020-05-21 17:31:12
fix script e864e72a9b1fd0e6dfe200b3a9b569016f9894c0 Thai Thien 2020-05-21 17:24:38
rename 4f5e84a74bfd4f2a4f60554b9037eb097bafb0df Thai Thien 2020-05-21 17:23:08
implement the main flow f31d93a1f3f78575c9ee06bc47b541007789643a Thai Thien 2020-05-21 17:16:52
script 4d177e367c6609a0592525ee44b32bcbe43536a6 Thai Thien 2020-05-19 16:30:08
python code to split train data to train and validate 0dfb94063b0bdc7aa660b78ab61b9ee5e61a4199 Thai Thien 2020-05-18 16:19:21
fix dim mismatch 93ea7669d891301e9c00aadccdea27bb5e138656 Thai Thien 2020-05-12 17:19:33
train h1 bigtail ea6391257cd243098cbbb771e705f1f115b845df Thai Thien 2020-05-12 16:58:26
mse mean e96c22a36e305681d7fed415a5a949fa0c1791c9 Thai Thien 2020-05-10 18:32:02
no fix 7bd97e91de5d7c2d307407287c82e60e893c0c92 Thai Thien 2020-05-10 18:22:45
no fix fc20ae6922c2e53f7d37f4228fb921894cd78eab Thai Thien 2020-05-10 18:19:59
t9 d8ef865ea602670548e897d8b7ac4c925cc9b393 Thai Thien 2020-05-10 18:19:30
test with L1 loss 6492b65da4bdf6351b661f39b6bce6f08d37f17c Thai Thien 2020-05-10 18:10:49
H2 1d6d11b2eeecb67dd7d329e38de61b872870a9aa Thai Thien 2020-05-06 17:42:52
do something with l1 loss 5268c4fc163bb512f293fbac381a64a75c4fe462 Thai Thien 2020-05-06 17:32:45
typo b7b8e2303ce99b2196402ec93334598598e71e5a Thai Thien 2020-05-05 17:32:31
increase epoch 67f89509e4294c4310b42e790425c82279df16b3 Thai Thien 2020-05-05 17:25:17
Commit be343dcc3b65f15f30e395eac3ca8271c09d1634 - log some more
Author: Thai Thien
Author date (UTC): 2020-05-21 17:43
Committer name: Thai Thien
Committer date (UTC): 2020-05-21 17:43
Parent(s): 57ca8f68cbb0b650da74f7117ee60bd25bf0d8d4
Signing key:
Tree: 9bec4392b1ef8331d666b664b469bc78e9969fd4
File Lines added Lines deleted
experiment_main.py 6 1
File experiment_main.py changed (mode: 100644) (index b6adfc3..53441ce)
... ... if __name__ == "__main__":
223 223 flag_mse = best_mse.checkAndRecord(metrics['mse']) flag_mse = best_mse.checkAndRecord(metrics['mse'])
224 224
225 225 if flag_mae or flag_mse: if flag_mae or flag_mse:
226 experiment.log_metric("valid_best_mae", metrics['mae'])
227 experiment.log_metric("valid_best_mse", metrics['mse'])
228 experiment.log_metric("valid_best_epoch", trainer.state.epoch)
229 print("BEST VAL, evaluating on test set")
226 230 evaluate_test_timer.resume() evaluate_test_timer.resume()
227 231 evaluator_test.run(test_loader) evaluator_test.run(test_loader)
228 232 evaluate_test_timer.pause() evaluate_test_timer.pause()
 
... ... if __name__ == "__main__":
234 238 experiment.log_metric("test_mae", test_metrics['mae']) experiment.log_metric("test_mae", test_metrics['mae'])
235 239 experiment.log_metric("test_mse", test_metrics['mse']) experiment.log_metric("test_mse", test_metrics['mse'])
236 240 experiment.log_metric("test_loss", test_metrics['loss']) experiment.log_metric("test_loss", test_metrics['loss'])
237 experiment.log_metric("valid_best_epoch", trainer.state.epoch)
241
242
238 243
239 244
240 245 def checkpoint_valid_mae_score_function(engine): def checkpoint_valid_mae_score_function(engine):
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