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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)
small tall on split branch	36c80eee740df7449c112f4dd4925e0ffbc7ac5a	Thai Thien	2020-04-13 15:23:33
fix load model	68c03563a5aa3acda165eae104ff4d2df83201b2	Thai Thien	2020-04-09 17:30:14
get lr and weight_decay	b43666da2cb8bb5710f30d0f3bfd2c3b1e7b6473	Thai Thien	2020-04-09 17:26:13
1201 epoch (because cur epoch continue when load)	ee303fe3945fcc6cc3c26601039de77a58fa3d60	Thai Thien	2020-04-09 17:23:18
shb load model	062126f959c021577dbf08224aeb442ca308587c	Thai Thien	2020-04-09 17:20:27
4	2f49bfa380e997c177af1de34c8d6882ed7099e9	Thai Thien	2020-04-09 17:06:28
11	331644c623b1bf5a34c4db432e1526f6bc34a398	Thai Thien	2020-04-09 17:04:49
batchsize 24	f6aeba845ee1915cb0aeb8fce298e56a6ba40b3a	Thai Thien	2020-04-09 16:46:25
t10	91d9e83c80a6a533535fd91278b9175c839c9715	Thai Thien	2020-04-09 16:43:38
t9	927b97f2f285000ce7b407496c52da2c61539cb8	Thai Thien	2020-04-09 16:37:39
minor bugfix	cbab75b39a2d3495c1d07a6f5c127ccc6e7cfbf5	Thai Thien	2020-04-09 16:15:24
ccnn v2 t89 shb	15fca0fdfa56fb6abe4928642fbaf8b444fa5fbb	Thai Thien	2020-04-09 15:46:00
fixed: not discard under-size in 256	8a0ef0a9bfb0801933dd4403685fe65ebb5dac6a	Thai Thien	2020-04-08 16:10:46
data_flow fixed 256, we ignore too small image in Batch for now	34a56f59674dee5267dba356b3ebe469baa91baf	Thai Thien	2020-04-08 15:46:34
fix typo	e9e5fe46043233c703e0a872afd1510434d4b5b0	Thai Thien	2020-04-07 18:49:20
tryting to reproduce ccnn again	b3681bbf85bb50eb5430581d8779415520d78dc2	Thai Thien	2020-04-07 18:25:30
fix bug, new dataflow	28706ac8dd35ff6f7d17c7d01656b047dd95cffe	Thai Thien	2020-04-07 17:54:57
ccnn_v2_t2_sha_scheduler	0bd4b83a3e2adb4d054537fde38c56ec3eca0d68	Thai Thien	2020-04-07 02:16:53
lower ccnn sgd lr	9f10c1c664cf9be2b3093ba72815740b31521287	Thai Thien	2020-04-06 17:41:39
5	07b51e18899506183b197366b8a2e6319dec0215	Thai Thien	2020-04-06 17:30:33

Commit 36c80eee740df7449c112f4dd4925e0ffbc7ac5a - small tall on split branch
Author: Thai Thien
Author date (UTC): 2020-04-13 15:23
Committer name: Thai Thien
Committer date (UTC): 2020-04-13 15:23
Parent(s): 68c03563a5aa3acda165eae104ff4d2df83201b2
Signing key:
Tree: 16a7beeba353b90282a210e13b0bd4f49f3e8026

File	Lines added	Lines deleted
experiment_meow_main.py	3	1
models/meow_experiment/ccnn_tail.py	45	0
train_script/meow_one/big_tail/bigtail1_t1_sha.sh	0	0
train_script/meow_one/big_tail/bigtail1_t2_sha.sh	0	0
train_script/meow_one/big_tail/bigtail2_t1_sha.sh	0	0
train_script/meow_one/big_tail/bigtail2_t2_sha.sh	0	0
train_script/meow_one/big_tail/bigtail3_t1_sha.sh	13	0
train_script/meow_one/big_tail/bigtail3_t1_shb.sh	14	0
train_script/meow_one/big_tail/bigtail3_t2_shb.sh	14	0

File experiment_meow_main.py changed (mode: 100644) (index 6e113ad..19ff638)
...	...	from visualize_util import get_readable_time
11	11	import torch	import torch
12	12	from torch import nn	from torch import nn
13	13	from models.meow_experiment.kitten_meow_1 import M1, M2, M3	from models.meow_experiment.kitten_meow_1 import M1, M2, M3
14		from models.meow_experiment.ccnn_tail import BigTailM1, BigTailM2
	14		from models.meow_experiment.ccnn_tail import BigTailM1, BigTailM2, BigTail3
15	15	from models import CustomCNNv2	from models import CustomCNNv2
16	16	import os	import os
17	17	from model_util import get_lr	from model_util import get_lr

...	...	if __name__ == "__main__":
72	72	model = BigTailM1()	model = BigTailM1()
73	73	elif model_name == "BigTailM2":	elif model_name == "BigTailM2":
74	74	model = BigTailM2()	model = BigTailM2()
	75		elif model_name == "BigTail3":
	76		model = BigTail3()
75	77	else:	else:
76	78	print("error: you didn't pick a model")	print("error: you didn't pick a model")
77	79	exit(-1)	exit(-1)

File models/meow_experiment/ccnn_tail.py changed (mode: 100644) (index 926b13f..ee9a716)
...	...	class BigTailM2(nn.Module):
102	102	return x	return x
103	103
104	104
	105		class BigTail3(nn.Module):
	106		"""
	107		we set max tail at 60 only
	108		"""
	109		def __init__(self, load_weights=False):
	110		super(BigTailM2, self).__init__()
	111		self.model_note = "small taill 100"
	112		self.red_cnn = nn.Conv2d(3, 10, 9, padding=4)
	113		self.green_cnn = nn.Conv2d(3, 14, 7, padding=3)
	114		self.blue_cnn = nn.Conv2d(3, 16, 5, padding=2)
	115
	116		self.max_pooling = nn.MaxPool2d(kernel_size=2, stride=2)
	117
	118		self.c0 = nn.Conv2d(40, 60, 3, padding=2, dilation=2)
	119		self.c1 = nn.Conv2d(60, 60, 3, padding=2, dilation=2)
	120		self.c2 = nn.Conv2d(60, 60, 3, padding=2, dilation=2)
	121		self.c3 = nn.Conv2d(60, 30, 3, padding=2, dilation=2)
	122		self.c4 = nn.Conv2d(30, 15, 3, padding=2, dilation=2)
	123		self.c5 = nn.Conv2d(15, 10, 3, padding=2, dilation=2)
	124		self.output = nn.Conv2d(10, 1, 1)
	125
	126		def forward(self,x):
	127		x_red = self.max_pooling(F.relu(self.red_cnn(x), inplace=True))
	128		x_green = self.max_pooling(F.relu(self.green_cnn(x), inplace=True))
	129		x_blue = self.max_pooling(F.relu(self.blue_cnn(x), inplace=True))
	130
	131		x = torch.cat((x_red, x_green, x_blue), 1)
	132		x = F.relu(self.c0(x), inplace=True)
	133
	134		x = F.relu(self.c1(x), inplace=True)
	135
	136		x = F.relu(self.c2(x), inplace=True)
	137		x = self.max_pooling(x)
	138
	139		x = F.relu(self.c3(x), inplace=True)
	140		x = self.max_pooling(x)
	141
	142		x = F.relu(self.c4(x), inplace=True)
	143
	144		x = F.relu(self.c5(x), inplace=True)
	145
	146		x = self.output(x)
	147		return x
	148
	149

File train_script/meow_one/big_tail/bigtail1_t1_sha.sh renamed from train_script/meow_one/bigtail1_t1_sha.sh (similarity 100%)

File train_script/meow_one/big_tail/bigtail1_t2_sha.sh renamed from train_script/meow_one/bigtail1_t2_sha.sh (similarity 100%)

File train_script/meow_one/big_tail/bigtail2_t1_sha.sh renamed from train_script/meow_one/bigtail2_t1_sha.sh (similarity 100%)

File train_script/meow_one/big_tail/bigtail2_t2_sha.sh renamed from train_script/meow_one/bigtail2_t2_sha.sh (similarity 100%)

File train_script/meow_one/big_tail/bigtail3_t1_sha.sh added (mode: 100644) (index 0000000..07fbc9d)
	1	task="bigtail3_t1_sha"
	2
	3	CUDA_VISIBLE_DEVICES=2 HTTPS_PROXY="http://10.60.28.99:86" nohup python experiment_meow_main.py \
	4	--task_id $task \
	5	--note "bigtail3 shanghaitech_rnd" \
	6	--model "BigTail3" \
	7	--input /data/rnd/thient/thient_data/ShanghaiTech/part_B \
	8	--lr 1e-4 \
	9	--decay 1e-4 \
	10	--datasetname shanghaitech_20p \
	11	--epochs 602 > logs/$task.log &
	12
	13	echo logs/$task.log # for convenience

File train_script/meow_one/big_tail/bigtail3_t1_shb.sh added (mode: 100644) (index 0000000..496a43f)
	1	task="bigtail3_t1_shb"
	2
	3	CUDA_VISIBLE_DEVICES=1 HTTPS_PROXY="http://10.60.28.99:86" nohup python experiment_meow_main.py \
	4	--task_id $task \
	5	--note "bigtail3 shanghaitech_rnd" \
	6	--model "BigTail3" \
	7	--input /data/rnd/thient/thient_data/ShanghaiTech/part_B \
	8	--lr 1e-4 \
	9	--decay 1e-4 \
	10	--batchsize 8 \
	11	--datasetname shanghaitech_rnd \
	12	--epochs 301 > logs/$task.log &
	13
	14	echo logs/$task.log # for convenience

File train_script/meow_one/big_tail/bigtail3_t2_shb.sh added (mode: 100644) (index 0000000..5b63d8a)
	1	task="bigtail3_t2_shb"
	2
	3	CUDA_VISIBLE_DEVICES=3 HTTPS_PROXY="http://10.60.28.99:86" nohup python experiment_meow_main.py \
	4	--task_id $task \
	5	--note "bigtail3 shanghaitech_rnd e-5 lr" \
	6	--model "BigTail3" \
	7	--input /data/rnd/thient/thient_data/ShanghaiTech/part_B \
	8	--lr 1e-5 \
	9	--decay 1e-5 \
	10	--batchsize 8 \
	11	--datasetname shanghaitech_rnd \
	12	--epochs 301 > logs/$task.log &
	13
	14	echo logs/$task.log # for convenience

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