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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

List of commits:

Subject	Hash	Author	Date (UTC)
skip evaluate on training set	a38d5731a9d6209bc98a9cca0ad023b4798c68d5	Thai Thien	2020-05-28 16:15:29
t7	ac1f0d71c2d3e0a01241622c639a9090a5b3c427	Thai Thien	2020-05-28 15:55:56
rename	4e9754c3dff98577616d3f043f7f260aeef40ac6	Thai Thien	2020-05-27 15:54:54
not use gpu2	8324400a3d65c58cfdd5a63b0a940217f3277769	Thai Thien	2020-05-27 15:54:11
remove call loss in eval	06f13484f24b85b12cab15e5af16db4d086db497	Thai Thien	2020-05-27 15:52:44
expermient, bug fix	e83e7e058b6f1d7ec1237677a2d4770f1f788ea0	Thai Thien	2020-05-27 15:43:58
surpress python warning	82806340334b3beb9916b34bb00a66381ce57aae	Thai Thien	2020-05-26 12:00:49
sha total crop no keepfull	d0783ddab88ed042607738fb665b34028d485d0d	Thai Thien	2020-05-26 11:49:10
sha 60p	d5146c9f28b62fac137a15c862d99e1af30ce5fa	Thai Thien	2020-05-25 17:28:12
t12	35b7a40082505da5f79caf4cc16023144e18a7d8	Thai Thien	2020-05-24 12:00:45
add sha 20p random	597c821a0103344b5e3b7b80eb2f61c335275ed2	Thai Thien	2020-05-24 11:52:18
h2 t3 shb	babec8c08d4aebd8af14558eddfa2898918ff152	Thai Thien	2020-05-23 16:49:58
y_pred	e1c1e8096230344dabfc1c85ccae832ba08aaad6	Thai Thien	2020-05-23 16:37:24
when not train, return img and true count	93d3b48fc1cd3a5b43ac0e8782c57f2ea00a48bc	Thai Thien	2020-05-23 16:33:00
map->mat	c64a1548b1e9745c109c211f76e8dc2554cf6747	Thai Thien	2020-05-23 16:27:48
fix wrong file name	950ad302d9b0ec6ed04fb4d4a870087dda57281c	Thai Thien	2020-05-23 16:17:30
fix scipy.io	766d0f3ba48e0c3e0d2562136c5549e20070b805	Thai Thien	2020-05-23 15:44:44
h2 t3	358234af05d250dfccada3b281cd61749ee6c6e4	Thai Thien	2020-05-23 15:37:36
update experiment_main	e87e1f9e3f0ebe12201c86f61b14a95b9552c199	Thai Thien	2020-05-23 14:58:28
fix checkAndRecord, add gt count to test data loader	4290b7bb534ef0f785757b508c8e839ec6b3f9dc	Thai Thien	2020-05-23 14:38:51

Commit a38d5731a9d6209bc98a9cca0ad023b4798c68d5 - skip evaluate on training set
Author: Thai Thien
Author date (UTC): 2020-05-28 16:15
Committer name: Thai Thien
Committer date (UTC): 2020-05-28 16:15
Parent(s): ac1f0d71c2d3e0a01241622c639a9090a5b3c427
Signer:
Signing key:
Signing status: N
Tree: 64b9c6c38c1e9227ffda8125c40a5dbe0a3020a9

File	Lines added	Lines deleted
experiment_main.py	17	16
train_script/meow_one/big_tail/bigtail3_t8_sha.sh	1	1

File experiment_main.py changed (mode: 100644) (index 621b61e..77ead9f)
...	...	if __name__ == "__main__":
184	184
185	185	@trainer.on(Events.EPOCH_COMPLETED)	@trainer.on(Events.EPOCH_COMPLETED)
186	186	def log_training_results(trainer):	def log_training_results(trainer):
187		evaluator_train.run(train_loader_eval)
188		metrics = evaluator_train.state.metrics
189		timestamp = get_readable_time()
190		print(timestamp + " Training set Results - Epoch: {} Avg mae: {:.2f} Avg mse: {:.2f} Avg loss: {:.2f}"
191		.format(trainer.state.epoch, metrics['mae'], metrics['mse'], 0))
192		experiment.log_metric("epoch", trainer.state.epoch)
193		experiment.log_metric("train_mae", metrics['mae'])
194		experiment.log_metric("train_mse", metrics['mse'])
195		# experiment.log_metric("train_loss", metrics['loss'])
196		experiment.log_metric("lr", get_lr(optimizer))
197
198		experiment.log_metric("batch_timer", batch_timer.value())
199		experiment.log_metric("train_timer", train_timer.value())
200
201		print("batch_timer ", batch_timer.value())
202		print("train_timer ", train_timer.value())
	187		if not args.skip_train_eval:
	188		evaluator_train.run(train_loader_eval)
	189		metrics = evaluator_train.state.metrics
	190		timestamp = get_readable_time()
	191		print(timestamp + " Training set Results - Epoch: {} Avg mae: {:.2f} Avg mse: {:.2f} Avg loss: {:.2f}"
	192		.format(trainer.state.epoch, metrics['mae'], metrics['mse'], 0))
	193		experiment.log_metric("epoch", trainer.state.epoch)
	194		experiment.log_metric("train_mae", metrics['mae'])
	195		experiment.log_metric("train_mse", metrics['mse'])
	196		# experiment.log_metric("train_loss", metrics['loss'])
	197		experiment.log_metric("lr", get_lr(optimizer))
	198
	199		experiment.log_metric("batch_timer", batch_timer.value())
	200		experiment.log_metric("train_timer", train_timer.value())
	201
	202		print("batch_timer ", batch_timer.value())
	203		print("train_timer ", train_timer.value())
203	204
204	205	@trainer.on(Events.EPOCH_COMPLETED)	@trainer.on(Events.EPOCH_COMPLETED)
205	206	def log_validation_results(trainer):	def log_validation_results(trainer):

File train_script/meow_one/big_tail/bigtail3_t8_sha.sh copied from file train_script/meow_one/big_tail/bigtail3_t7_sha.sh (similarity 95%) (mode: 100644) (index 9503373..6b2784e)
1		task="bigtail3_t7_sha"
	1		task="bigtail3_t8_sha"
2	2
3	3	CUDA_VISIBLE_DEVICES=4 OMP_NUM_THREADS=2 PYTHONWARNINGS="ignore" HTTPS_PROXY="http://10.60.28.99:86" nohup python experiment_main.py \	CUDA_VISIBLE_DEVICES=4 OMP_NUM_THREADS=2 PYTHONWARNINGS="ignore" HTTPS_PROXY="http://10.60.28.99:86" nohup python experiment_main.py \
4	4	--task_id $task \	--task_id $task \

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