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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

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List of commits:

Subject	Hash	Author	Date (UTC)
WIP	fce5736b0f6104fa3549884fbaa1f6508086af06	Thai Thien	2020-08-03 17:14:11
debug sha keepful	e14c3307499356c7a7ed0d5f33818bd798276d94	Thai Thien	2020-08-03 15:44:02
adamw2_bigtail13i_t3_sha	f769948ddd511865f62cddc80957663508e25976	Thai Thien	2020-08-02 04:25:08
g	56048b30fb4a19ae52c641b07754756f43ddcefb	Thai Thien	2020-08-02 04:00:46
a	d4e0e0d63613536a18f7ae0f39e4798f12abe7e8	Thai Thien	2020-08-02 03:59:14
adamw1_bigtail13i_t4_sha	bc07d19cfcc88c4271d1c6f1984c1c96ff5a9413	Thai Thien	2020-08-01 16:19:17
adamw1_bigtail13i_t3_sha	17c169d6ef648e8c4f2c5383fb9226cfce48d626	Thai Thien	2020-08-01 16:11:33
adamw1_bigtail13i_t2_sha	8bc23f1401eacdc2e28f30a825503f0dd96bacc9	Thai Thien	2020-08-01 15:59:29
adamw1_bigtail13i_t2_shb	aadc7244daabdad64a548342865a22beda073d94	Thai Thien	2020-08-01 15:47:08
gpu4	95c356f61c49d9f1927da7f86135a9bb60d21a59	Thai Thien	2020-08-01 14:46:30
adamw1_bigtail13i_t1_sha	34434bd013a4b05134c5ce42aa8f9956d424467d	Thai Thien	2020-08-01 14:44:56
a	140443bb072f8086b6cef253bcadfb0d925ba606	Thai Thien	2020-08-01 12:09:09
adamw	57f61e52a024e91f57347c85a8c14813df16d15d	Thai Thien	2020-08-01 12:05:36
adam1_bigtail13i_t1_shb	713dd1d5a0f13a2c881b00687fabb1174383da5b	Thai Thien	2020-08-01 10:22:17
g1_BigTail14i_t8_sha	eb361a5e64d38062fa6e5aa61ae21adc5a536aef	Thai Thien	2020-07-31 15:45:50
g1_BigTail14i_t7_sha	32ff746fa0c272af36eadcd713cda94ef8f1b8e2	Thai Thien	2020-07-31 14:57:15
g1_BigTail14i_t6_sha	0656f2ac088bd2790b560931839bfa1d4bed98c4	Thai Thien	2020-07-30 19:32:13
sgd -6 g1_BigTail14i_t6_sha.sh	4c2877d478c40382109800e5a4b873d7a11b345c	Thai Thien	2020-07-30 19:29:58
t5	070bf50a1a9bba8b8406c5c58b5806e39e99b56e	Thai Thien	2020-07-30 19:26:48
g1_BigTail14i_t4_sha	71b259dab3cec69c9b40944cfe9e83ee723c8675	Thai Thien	2020-07-30 19:21:34

Commit fce5736b0f6104fa3549884fbaa1f6508086af06 - WIP
Author: Thai Thien
Author date (UTC): 2020-08-03 17:14
Committer name: Thai Thien
Committer date (UTC): 2020-08-03 17:14
Parent(s): e14c3307499356c7a7ed0d5f33818bd798276d94
Signing key:
Tree: 4d320d8bed5851bf90e024d5ec881944c25afbb3

File	Lines added	Lines deleted
debug/verify_model_shb_best.py	48	0

File debug/verify_model_shb_best.py added (mode: 100644) (index 0000000..120e444)
	1	import torch
	2	from models.meow_experiment.ccnn_tail import BigTail11i, BigTail10i, BigTail12i, BigTail13i, BigTail14i, BigTail15i
	3	from hard_code_variable import HardCodeVariable
	4	from data_util import ShanghaiTechDataPath
	5	from visualize_util import save_img, save_density_map
	6	import os
	7	from data_flow import get_train_val_list, get_dataloader, create_training_image_list
	8
	9	def visualize_evaluation_shanghaitech_keepfull(model):
	10	model = model.cuda()
	11	model.eval()
	12	HARD_CODE = HardCodeVariable()
	13	shanghaitech_data = ShanghaiTechDataPath(root=HARD_CODE.SHANGHAITECH_PATH)
	14	shanghaitech_data_part_a_train = shanghaitech_data.get_a().get_train().get()
	15	saved_folder = "visualize/evaluation_dataloader_shanghaitech"
	16	os.makedirs(saved_folder, exist_ok=True)
	17	train_list, val_list = get_train_val_list(shanghaitech_data_part_a_train, test_size=0.2)
	18	test_list = None
	19	train_loader, val_loader, test_loader = get_dataloader(train_list, val_list, test_list, dataset_name="shanghaitech_keepfull", visualize_mode=False,
	20	debug=True)
	21
	22	# do with train loader
	23	train_loader_iter = iter(train_loader)
	24	for i in range(10):
	25	img, label, count = next(train_loader_iter)
	26	# save_img(img, os.path.join(saved_folder, "train_img_" + str(i) +".png"))
	27	save_path = os.path.join(saved_folder, "train_label_" + str(i) +".png")
	28	save_pred_path = os.path.join(saved_folder, "train_pred_" + str(i) +".png")
	29	save_density_map(label.numpy()[0][0], save_path)
	30	pred = model(img.cuda())
	31	predicted_density_map = pred.detach().cpu().clone().numpy()
	32	save_density_map(predicted_density_map[0][0], save_pred_path)
	33	print("pred " + save_pred_path + " value " + str(predicted_density_map.sum()))
	34
	35
	36	"""
	37	Document on save load model
	38	https://pytorch.org/tutorials/beginner/saving_loading_models.html
	39	"""
	40
	41	model_path = "/data/save_model/adamw1_bigtail13i_t1_shb/adamw1_bigtail13i_t1_shb_checkpoint_valid_mae=-7.574910521507263.pth"
	42	checkpoint = torch.load(model_path)
	43
	44	model = BigTail13i()
	45	model.load_state_dict(checkpoint["model"])
	46	print("done load")
	47	visualize_evaluation_shanghaitech_keepfull(model)
	48

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